Author: "Graciá-Carpio, J." - Searchworks@Jio Institute Digital Library Search Results

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376 results on '"Graciá-Carpio, J."'

1. Euclid preparation. The impact of relativistic redshift-space distortions on two-point clustering statistics from the Euclid wide spectroscopic survey

Author: Euclid Collaboration, Elkhashab, M. Y., Bertacca, D., Porciani, C., Salvalaggio, J., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, R., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Schirmer, M., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Sefusatti, E., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., Finelli, F., Gracia-Carpio, J., Mauri, N., Pezzotta, A., Pöntinen, M., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Balaguera-Antolinez, A., Ballardini, M., Blanchard, A., Blot, L., Böhringer, H., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castro, T., Chambers, K. C., Cooray, A. R., Davini, S., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Hall, A., Hartley, W. G., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Lacasa, F., Graet, J. Le, Legrand, L., Loureiro, A., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Moretti, C., Morgante, G., Nadathur, S., Walton, Nicholas A., Patrizii, L., Popa, V., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Schneider, A., Sereno, M., Sikkema, G., Silvestri, A., Simon, P., Mancini, A. Spurio, Tanidis, K., Tao, C., Tessore, N., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Vernizzi, F., Verza, G., Vielzeuf, P., and Hernández-Monteagudo, C.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Measurements of galaxy clustering are affected by RSD. Peculiar velocities, gravitational lensing, and other light-cone projection effects modify the observed redshifts, fluxes, and sky positions of distant light sources. We determine which of these effects leave a detectable imprint on several 2-point clustering statistics extracted from the EWSS on large scales. We generate 140 mock galaxy catalogues with the survey geometry and selection function of the EWSS and make use of the LIGER method to account for a variable number of relativistic RSD to linear order in the cosmological perturbations. We estimate different 2-point clustering statistics from the mocks and use the likelihood-ratio test to calculate the statistical significance with which the EWSS could reject the null hypothesis that certain relativistic projection effects can be neglected in the theoretical models. We find that the combined effects of lensing magnification and convergence imprint characteristic signatures on several clustering observables. Their S/N ranges between 2.5 and 6 (depending on the adopted summary statistic) for the highest-redshift galaxies in the EWSS. The corresponding feature due to the peculiar velocity of the Sun is measured with a S/N of order one or two. The $P_{\ell}(k)$ from the catalogues that include all relativistic effects reject the null hypothesis that RSD are only generated by the variation of the peculiar velocity along the line of sight with a significance of 2.9 standard deviations. As a byproduct of our study, we demonstrate that the mixing-matrix formalism to model finite-volume effects in the $P_{\ell}(k)$ can be robustly applied to surveys made of several disconnected patches. Our results indicate that relativistic RSD, the contribution from weak gravitational lensing in particular, cannot be disregarded when modelling 2-point clustering statistics extracted from the EWSS., Comment: 23 pages, 14 figures
Published: 2024

2. Euclid preparation: 6x2 pt analysis of Euclid's spectroscopic and photometric data sets

Author: Euclid Collaboration, Paganin, L., Bonici, M., Carbone, C., Camera, S., Tutusaus, I., Davini, S., Bel, J., Tosi, S., Sciotti, D., Di Domizio, S., Risso, I., Testera, G., Sapone, D., Sakr, Z., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Bardelli, S., Battaglia, P., Bender, R., Bernardeau, F., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Costille, A., Courbin, F., Courtois, H. M., Crocce, M., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., George, K., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Ilić, S., Jahnke, K., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Steinwagner, J., Surace, C., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Fabbian, G., Farinelli, R., Graciá-Carpio, J., Mauri, N., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Ballardini, M., Blanchard, A., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castro, T., Cañas-Herrera, G., Chambers, K. C., Contarini, S., Cooray, A. R., Coupon, J., Desprez, G., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferreira, P. G., Ferrero, I., Finelli, F., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Gregorio, A., Hall, A., Hildebrandt, H., Hjorth, J., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Rocci, P. -F., Sahlén, M., Schneider, A., Schultheis, M., Sereno, M., Tao, C., Tessore, N., Teyssier, R., Toft, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., and Vielzeuf, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present cosmological parameter forecasts for the Euclid 6x2pt statistics, which include the galaxy clustering and weak lensing main probes together with previously neglected cross-covariance and cross-correlation signals between imaging/photometric and spectroscopic data. The aim is understanding the impact of such terms on the Euclid performance. We produce 6x2pt cosmological forecasts, considering two different techniques: the so-called harmonic and hybrid approaches, respectively. In the first, we treat all the different Euclid probes in the same way, i.e. we consider only angular 2pt-statistics for spectroscopic and photometric clustering, as well as for weak lensing, analysing all their possible cross-covariances and cross-correlations in the spherical harmonic domain. In the second, we do not account for negligible cross-covariances between the 3D and 2D data, but consider the combination of their cross-correlation with the auto-correlation signals. We find that both cross-covariances and cross-correlation signals, have a negligible impact on the cosmological parameter constraints and, therefore, on the Euclid performance. In the case of the hybrid approach, we attribute this result to the effect of the cross-correlation between weak lensing and photometric data, which is dominant with respect to other cross-correlation signals. In the case of the 2D harmonic approach, we attribute this result to two main theoretical limitations of the 2D projected statistics implemented in this work according to the analysis of official Euclid forecasts: the high shot noise and the limited redshift range of the spectroscopic sample, together with the loss of radial information from subleading terms such as redshift-space distortions and lensing magnification. Our analysis suggests that 2D and 3D Euclid data can be safely treated as independent, with a great saving in computational resources., Comment: 32 pages, 20 figures. Comments are welcome
Published: 2024

3. Euclid preparation. Deep learning true galaxy morphologies for weak lensing shear bias calibration

Author: Euclid Collaboration, Csizi, B., Schrabback, T., Grandis, S., Hoekstra, H., Jansen, H., Linke, L., Congedo, G., Taylor, A. N., Amara, A., Andreon, S., Baccigalupi, C., Baldi, M., Bardelli, S., Battaglia, P., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Faustini, F., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Ilić, S., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sánchez, A. G., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Tavagnacco, D., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., Gracia-Carpio, J., Matthew, S., Mauri, N., Pezzotta, A., Pöntinen, M., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Ballardini, M., Blanchard, A., Blot, L., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Cañas-Herrera, G., Cappi, A., Caro, F., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gasparetto, T., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Gutierrez, C. M., Hall, A., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Brun, A. M. C. Le, Graet, J. Le, Legrand, L., Lesgourgues, J., Liaudat, T. I., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martín-Fleitas, J., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Miluzio, M., Monaco, P., Montoro, A., Mora, A., Moretti, C., Morgante, G., Walton, Nicholas A., Pagano, L., Patrizii, L., Popa, V., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Sarpa, E., Schneider, A., Sereno, M., Simon, P., Mancini, A. Spurio, Stadel, J., Tanidis, K., Tao, C., Tessore, N., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., and Vielzeuf, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: To date, galaxy image simulations for weak lensing surveys usually approximate the light profiles of all galaxies as a single or double S\'ersic profile, neglecting the influence of galaxy substructures and morphologies deviating from such a simplified parametric characterization. While this approximation may be sufficient for previous data sets, the stringent cosmic shear calibration requirements and the high quality of the data in the upcoming Euclid survey demand a consideration of the effects that realistic galaxy substructures have on shear measurement biases. Here we present a novel deep learning-based method to create such simulated galaxies directly from HST data. We first build and validate a convolutional neural network based on the wavelet scattering transform to learn noise-free representations independent of the point-spread function of HST galaxy images that can be injected into simulations of images from Euclid's optical instrument VIS without introducing noise correlations during PSF convolution or shearing. Then, we demonstrate the generation of new galaxy images by sampling from the model randomly and conditionally. Next, we quantify the cosmic shear bias from complex galaxy shapes in Euclid-like simulations by comparing the shear measurement biases between a sample of model objects and their best-fit double-S\'ersic counterparts. Using the KSB shape measurement algorithm, we find a multiplicative bias difference between these branches with realistic morphologies and parametric profiles on the order of $6.9\times 10^{-3}$ for a realistic magnitude-S\'ersic index distribution. Moreover, we find clear detection bias differences between full image scenes simulated with parametric and realistic galaxies, leading to a bias difference of $4.0\times 10^{-3}$ independent of the shape measurement method. This makes it relevant for stage IV weak lensing surveys such as Euclid., Comment: Submitted to A&A. 29 pages, 20 figures, 2 tables
Published: 2024

4. Euclid preparation. Simulations and nonlinearities beyond $\Lambda$CDM. 4. Constraints on $f(R)$ models from the photometric primary probes

Author: Euclid Collaboration, Koyama, K., Pamuk, S., Casas, S., Bose, B., Carrilho, P., Sáez-Casares, I., Atayde, L., Cataneo, M., Fiorini, B., Giocoli, C., Brun, A. M. C. Le, Pace, F., Pourtsidou, A., Rasera, Y., Sakr, Z., Winther, H. -A., Altamura, E., Adamek, J., Baldi, M., Breton, M. -A., Rácz, G., Vernizzi, F., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Bardelli, S., Bernardeau, F., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Caillat, A., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Hailey, M., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Ilić, S., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Neissner, C., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Salvignol, J. -C., Sánchez, A. G., Sapone, D., Sartoris, B., Schirmer, M., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Fabbian, G., Farinelli, R., Finelli, F., Gracia-Carpio, J., Matthew, S., Mauri, N., Pezzotta, A., Pöntinen, M., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Ballardini, M., Bertacca, D., Blanchard, A., Blot, L., Böhringer, H., Bruton, S., Cabanac, R., Calabro, A., Quevedo, B. Camacho, Cañas-Herrera, G., Cappi, A., Caro, F., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ezziati, M., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gasparetto, T., Gautard, V., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Gutierrez, C. M., Hall, A., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Graet, J. Le, Legrand, L., Lesgourgues, J., Liaudat, T. I., Liu, S. J., Loureiro, A., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martín-Fleitas, J., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Miluzio, M., Monaco, P., Montoro, A., Mora, A., Moretti, C., Morgante, G., Murray, C., Nadathur, S., Walton, Nicholas A., Pagano, L., Patrizii, L., Popa, V., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Sarpa, E., Schneider, A., Sereno, M., Silvestri, A., Mancini, A. Spurio, Stadel, J., Tanidis, K., Tao, C., Tessore, N., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Vergani, D., Verza, G., and Vielzeuf, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We study the constraint on $f(R)$ gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical modelling of the nonlinear matter power spectrum. In the Hu-Sawicki $f(R)$ gravity model, we consider four different predictions for the ratio between the power spectrum in $f(R)$ and that in $\Lambda$CDM: a fitting formula, the halo model reaction approach, ReACT and two emulators based on dark matter only $N$-body simulations, FORGE and e-Mantis. These predictions are added to the MontePython implementation to predict the angular power spectra for weak lensing (WL), photometric galaxy clustering and their cross-correlation. By running Markov Chain Monte Carlo, we compare constraints on parameters and investigate the bias of the recovered $f(R)$ parameter if the data are created by a different model. For the pessimistic setting of WL, one dimensional bias for the $f(R)$ parameter, $\log_{10}|f_{R0}|$, is found to be $0.5 \sigma$ when FORGE is used to create the synthetic data with $\log_{10}|f_{R0}| =-5.301$ and fitted by e-Mantis. The impact of baryonic physics on WL is studied by using a baryonification emulator BCemu. For the optimistic setting, the $f(R)$ parameter and two main baryon parameters are well constrained despite the degeneracies among these parameters. However, the difference in the nonlinear dark matter prediction can be compensated by the adjustment of baryon parameters, and the one-dimensional marginalised constraint on $\log_{10}|f_{R0}|$ is biased. This bias can be avoided in the pessimistic setting at the expense of weaker constraints. For the pessimistic setting, using the $\Lambda$CDM synthetic data for WL, we obtain the prior-independent upper limit of $\log_{10}|f_{R0}|< -5.6$. Finally, we implement a method to include theoretical errors to avoid the bias., Comment: 24 pages, 16 figures, submitted on behalf of the Euclid Collaboration
Published: 2024

5. Euclid preparation. Simulations and nonlinearities beyond $\Lambda$CDM. 2. Results from non-standard simulations

Author: Euclid Collaboration, Rácz, G., Breton, M. -A., Fiorini, B., Brun, A. M. C. Le, Winther, H. -A., Sakr, Z., Pizzuti, L., Ragagnin, A., Gayoux, T., Altamura, E., Carella, E., Pardede, K., Verza, G., Koyama, K., Baldi, M., Pourtsidou, A., Vernizzi, F., Adame, A. G., Adamek, J., Avila, S., Carbone, C., Despali, G., Giocoli, C., Hernández-Aguayo, C., Hassani, F., Kunz, M., Li, B., Rasera, Y., Yepes, G., Gonzalez-Perez, V., Corasaniti, P. -S., García-Bellido, J., Hamaus, N., Kiessling, A., Marinucci, M., Moretti, C., Mota, D. F., Piga, L., Pisani, A., Szapudi, I., Tallada-Crespí, P., Aghanim, N., Andreon, S., Baccigalupi, C., Bardelli, S., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillis, B., Gómez-Alvarez, P., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Ilić, S., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kilbinger, M., Kitching, T., Kubik, B., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Salvignol, J. -C., Sánchez, A. G., Sapone, D., Sartoris, B., Schirmer, M., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Wang, Y., Weller, J., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Fabbian, G., Finelli, F., Gracia-Carpio, J., Matthew, S., Mauri, N., Pezzotta, A., Pöntinen, M., Porciani, C., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Balaguera-Antolinez, A., Ballardini, M., Bertacca, D., Blot, L., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Quevedo, B. Camacho, Cappi, A., Caro, F., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., Gasparetto, T., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Gutierrez, C. M., Hall, A., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Lacasa, F., Graet, J. Le, Legrand, L., Lesgourgues, J., Liaudat, T. I., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Miluzio, M., Monaco, P., Montoro, A., Mora, A., Morgante, G., Nadathur, S., Walton, Nicholas A., Patrizii, L., Popa, V., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Schneider, A., Sereno, M., Silvestri, A., Mancini, A. Spurio, Stadel, J., Tanidis, K., Tao, C., Tessore, N., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., and Vielzeuf, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Euclid mission will measure cosmological parameters with unprecedented precision. To distinguish between cosmological models, it is essential to generate realistic mock observables from cosmological simulations that were run in both the standard $\Lambda$-cold-dark-matter ($\Lambda$CDM) paradigm and in many non-standard models beyond $\Lambda$CDM. We present the scientific results from a suite of cosmological N-body simulations using non-standard models including dynamical dark energy, k-essence, interacting dark energy, modified gravity, massive neutrinos, and primordial non-Gaussianities. We investigate how these models affect the large-scale-structure formation and evolution in addition to providing synthetic observables that can be used to test and constrain these models with Euclid data. We developed a custom pipeline based on the Rockstar halo finder and the nbodykit large-scale structure toolkit to analyse the particle output of non-standard simulations and generate mock observables such as halo and void catalogues, mass density fields, and power spectra in a consistent way. We compare these observables with those from the standard $\Lambda$CDM model and quantify the deviations. We find that non-standard cosmological models can leave significant imprints on the synthetic observables that we have generated. Our results demonstrate that non-standard cosmological N-body simulations provide valuable insights into the physics of dark energy and dark matter, which is essential to maximising the scientific return of Euclid., Comment: 22 pages, 7 figures
Published: 2024

6. Euclid preparation. Simulations and nonlinearities beyond $\Lambda$CDM. 1. Numerical methods and validation

Author: Euclid Collaboration, Adamek, J., Fiorini, B., Baldi, M., Brando, G., Breton, M. -A., Hassani, F., Koyama, K., Brun, A. M. C. Le, Rácz, G., Winther, H. -A., Casalino, A., Hernández-Aguayo, C., Li, B., Potter, D., Altamura, E., Carbone, C., Giocoli, C., Mota, D. F., Pourtsidou, A., Sakr, Z., Vernizzi, F., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Bardelli, S., Battaglia, P., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Caillat, A., Camera, S., Capobianco, V., Cardone, V. F., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillis, B., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Ilić, S., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Neissner, C., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sánchez, A. G., Sapone, D., Sartoris, B., Schirmer, M., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Tavagnacco, D., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Fabbian, G., Finelli, F., Gracia-Carpio, J., Matthew, S., Mauri, N., Pezzotta, A., Pöntinen, M., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Balaguera-Antolinez, A., Ballardini, M., Blanchard, A., Blot, L., Böhringer, H., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Quevedo, B. Camacho, Cañas-Herrera, G., Cappi, A., Caro, F., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gasparetto, T., Gautard, V., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Gutierrez, C. M., Hall, A., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Kruk, S., Graet, J. Le, Legrand, L., Lesgourgues, J., Liaudat, T. I., Loureiro, A., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Migliaccio, M., Miluzio, M., Monaco, P., Montoro, A., Mora, A., Moretti, C., Morgante, G., Nadathur, S., Patrizii, L., Popa, V., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Sarpa, E., Schneider, A., Sereno, M., Silvestri, A., Mancini, A. Spurio, Tanidis, K., Tao, C., Tessore, N., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., Vielzeuf, P., and Walton, N. A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: To constrain models beyond $\Lambda$CDM, the development of the Euclid analysis pipeline requires simulations that capture the nonlinear phenomenology of such models. We present an overview of numerical methods and $N$-body simulation codes developed to study the nonlinear regime of structure formation in alternative dark energy and modified gravity theories. We review a variety of numerical techniques and approximations employed in cosmological $N$-body simulations to model the complex phenomenology of scenarios beyond $\Lambda$CDM. This includes discussions on solving nonlinear field equations, accounting for fifth forces, and implementing screening mechanisms. Furthermore, we conduct a code comparison exercise to assess the reliability and convergence of different simulation codes across a range of models. Our analysis demonstrates a high degree of agreement among the outputs of different simulation codes, providing confidence in current numerical methods for modelling cosmic structure formation beyond $\Lambda$CDM. We highlight recent advances made in simulating the nonlinear scales of structure formation, which are essential for leveraging the full scientific potential of the forthcoming observational data from the Euclid mission., Comment: 20 pages, 7 figures, 1 appendix; submitted on behalf of the Euclid Collaboration
Published: 2024

7. Euclid preparation: Determining the weak lensing mass accuracy and precision for galaxy clusters

Author: Euclid Collaboration, Ingoglia, L., Sereno, M., Farrens, S., Giocoli, C., Baumont, L., Lesci, G. F., Moscardini, L., Murray, C., Vannier, M., Biviano, A., Carbone, C., Covone, G., Despali, G., Maturi, M., Maurogordato, S., Meneghetti, M., Radovich, M., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Bardelli, S., Bellagamba, F., Bender, R., Bernardeau, F., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Faustini, F., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillard, W., Gillis, B., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Ilić, S., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Merlin, E., Meylan, G., Moresco, M., Munari, E., Niemi, S. -M., Padilla, C., Paech, K., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Salvignol, J. -C., Sánchez, A. G., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Bolzonella, M., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., Finelli, F., Gracia-Carpio, J., Matthew, S., Pezzotta, A., Pöntinen, M., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Ballardini, M., Bertacca, D., Bethermin, M., Blanchard, A., Blot, L., Böhringer, H., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Cañas-Herrera, G., Cappi, A., Caro, F., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., Costanzi, M., Cucciati, O., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ezziati, M., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gasparetto, T., Gautard, V., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Gutierrez, C. M., Hall, A., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Brun, A. M. C. Le, Graet, J. Le, Legrand, L., Lesgourgues, J., Liaudat, T. I., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martín-Fleitas, J., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Miluzio, M., Monaco, P., Montoro, A., Mora, A., Moretti, C., Morgante, G., Nadathur, S., Walton, Nicholas A., Pagano, L., Patrizii, L., Popa, V., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Sarpa, E., Schneider, A., Schultheis, M., Simon, P., Mancini, A. Spurio, Stadel, J., Stanford, S. A., Tanidis, K., Tao, C., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., and Vielzeuf, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We investigate the level of accuracy and precision of cluster weak-lensing (WL) masses measured with the \Euclid data processing pipeline. We use the DEMNUni-Cov $N$-body simulations to assess how well the WL mass probes the true halo mass, and, then, how well WL masses can be recovered in the presence of measurement uncertainties. We consider different halo mass density models, priors, and mass point estimates. WL mass differs from true mass due to, e.g., the intrinsic ellipticity of sources, correlated or uncorrelated matter and large-scale structure, halo triaxiality and orientation, and merging or irregular morphology. In an ideal scenario without observational or measurement errors, the maximum likelihood estimator is the most accurate, with WL masses biased low by $\langle b_M \rangle = -14.6 \pm 1.7 \, \%$ on average over the full range $M_\text{200c} > 5 \times 10^{13} \, M_\odot$ and $z < 1$. Due to the stabilising effect of the prior, the biweight, mean, and median estimates are more precise. The scatter decreases with increasing mass and informative priors significantly reduce the scatter. Halo mass density profiles with a truncation provide better fits to the lensing signal, while the accuracy and precision are not significantly affected. We further investigate the impact of additional sources of systematic uncertainty on the WL mass, namely the impact of photometric redshift uncertainties and source selection, the expected performance of \Euclid cluster detection algorithms, and the presence of masks. Taken in isolation, we find that the largest effect is induced by non-conservative source selection. This effect can be mostly removed with a robust selection. As a final \Euclid-like test, we combine systematic effects in a realistic observational setting and find results similar to the ideal case, $\langle b_M \rangle = - 15.5 \pm 2.4 \, \%$, under a robust selection.
Published: 2024

8. Euclid preparation. L. Calibration of the linear halo bias in $\Lambda(\nu)$CDM cosmologies

Author: Euclid Collaboration, Castro, T., Fumagalli, A., Angulo, R. E., Bocquet, S., Borgani, S., Costanzi, M., Dakin, J., Dolag, K., Monaco, P., Saro, A., Sefusatti, E., Aghanim, N., Amendola, L., Andreon, S., Baccigalupi, C., Baldi, M., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Caillat, A., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Costille, A., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Douspis, M., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Ilić, S., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Renzi, A., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sakr, Z., Salvignol, J. -C., Sánchez, A. G., Sapone, D., Sartoris, B., Schirmer, M., Secroun, A., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zucca, E., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Finelli, F., Gracia-Carpio, J., Matthew, S., Mauri, N., Pezzotta, A., Pöntinen, M., Porciani, C., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Balaguera-Antolinez, A., Ballardini, M., Bertacca, D., Bethermin, M., Blanchard, A., Blot, L., Böhringer, H., Bruton, S., Cabanac, R., Calabro, A., Cañas-Herrera, G., Cappi, A., Caro, F., Carvalho, C. S., Chambers, K. C., Cooray, A. R., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gasparetto, T., Gautard, V., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Gutierrez, C. M., Hall, A., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Brun, A. M. C. Le, Graet, J. Le, Legrand, L., Lesgourgues, J., Liaudat, T. I., Loureiro, A., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Miluzio, M., Montoro, A., Mora, A., Moretti, C., Morgante, G., Nadathur, S., Walton, Nicholas A., Pagano, L., Patrizii, L., Popa, V., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Sarpa, E., Schneider, A., Sereno, M., Mancini, A. Spurio, Stadel, J., Tanidis, K., Tao, C., Tessore, N., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., and Vielzeuf, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Euclid mission, designed to map the geometry of the dark Universe, presents an unprecedented opportunity for advancing our understanding of the cosmos through its photometric galaxy cluster survey. This paper focuses on enhancing the precision of halo bias (HB) predictions, which is crucial for deriving cosmological constraints from the clustering of galaxy clusters. Our study is based on the peak-background split (PBS) model linked to the halo mass function (HMF); it extends with a parametric correction to precisely align with results from an extended set of $N$-body simulations carried out with the OpenGADGET3 code. Employing simulations with fixed and paired initial conditions, we meticulously analyze the matter-halo cross-spectrum and model its covariance using a large number of mock catalogs generated with Lagrangian Perturbation Theory simulations with the PINOCCHIO code. This ensures a comprehensive understanding of the uncertainties in our HB calibration. Our findings indicate that the calibrated HB model is remarkably resilient against changes in cosmological parameters including those involving massive neutrinos. The robustness and adaptability of our calibrated HB model provide an important contribution to the cosmological exploitation of the cluster surveys to be provided by the Euclid mission. This study highlights the necessity of continuously refining the calibration of cosmological tools like the HB to match the advancing quality of observational data. As we project the impact of our model on cosmological constraints, we find that, given the sensitivity of the Euclid survey, a miscalibration of the HB could introduce biases in cluster cosmology analyses. Our work fills this critical gap, ensuring the HB calibration matches the expected precision of the Euclid survey. The implementation of our model is publicly available in https://github.com/TiagoBsCastro/CCToolkit., Comment: 20 pages; 12 figures; accepted for publication in A&A; abstract abridged for arXiv submission
Published: 2024

9. Euclid preparation. XLIX. Selecting active galactic nuclei using observed colours

Author: Euclid Collaboration, Bisigello, L., Massimo, M., Tortora, C., Fotopoulou, S., Allevato, V., Bolzonella, M., Gruppioni, C., Pozzetti, L., Rodighiero, G., Serjeant, S., Cunha, P. A. C., Gabarra, L., Feltre, A., Humphrey, A., La Franca, F., Landt, H., Mannucci, F., Prandoni, I., Radovich, M., Ricci, F., Salvato, M., Shankar, F., Stern, D., Spinoglio, L., Vergani, D., Vignali, C., Zamorani, G., Yung, L. Y. A., Charlot, S., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Battaglia, P., Bender, R., Bonino, D., Branchini, E., Brau-Nogue, S., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zoubian, J., Zucca, E., Biviano, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Fabbian, G., Graciá-Carpio, J., Marcin, S., Mauri, N., Sakr, Z., Scottez, V., Tenti, M., Akrami, Y., Baccigalupi, C., Ballardini, M., Bethermin, M., Blanchard, A., Borgani, S., Borla, A. S., Bruton, S., Burigana, C., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Coupon, A. R. Cooray J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Ganga, K., García-Bellido, J., Giacomini, F., Gozaliasl, G., Gregorio, A., Hildebrandt, H., Muñoz, A. Jiminez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mainetti, G., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sereno, M., Simon, P., Stadel, J., Stanford, S. A., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Viel, M., and Zinchenko, I. A.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Euclid will cover over 14000 $deg^{2}$ with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our understanding of galaxy evolution and AGN. In this work we identify the best colour selection criteria for AGN, based only on Euclid photometry or including ancillary photometric observations, such as the data that will be available with the Rubin legacy survey of space and time (LSST) and observations already available from Spitzer/IRAC. The analysis is performed for unobscured AGN, obscured AGN, and composite (AGN and star-forming) objects. We make use of the spectro-photometric realisations of infrared-selected targets at all-z (SPRITZ) to create mock catalogues mimicking both the Euclid Wide Survey (EWS) and the Euclid Deep Survey (EDS). Using these catalogues we estimate the best colour selection, maximising the harmonic mean (F1) of completeness and purity. The selection of unobscured AGN in both Euclid surveys is possible with Euclid photometry alone with F1=0.22-0.23, which can increase to F1=0.43-0.38 if we limit at z>0.7. Such selection is improved once the Rubin/LSST filters (a combination of the u, g, r, or z filters) are considered, reaching F1=0.84 and 0.86 for the EDS and EWS, respectively. The combination of a Euclid colour with the [3.6]-[4.5] colour, which is possible only in the EDS, results in an F1-score of 0.59, improving the results using only Euclid filters, but worse than the selection combining Euclid and LSST. The selection of composite ($f_{{\rm AGN}}$=0.05-0.65 at 8-40 $\mu m$) and obscured AGN is challenging, with F1<0.3 even when including ancillary data. This is driven by the similarities between the broad-band spectral energy distribution of these AGN and star-forming galaxies in the wavelength range 0.3-5 $\mu m$., Comment: 25 pages, 28 figures, accepted for publication on A&A
Published: 2024

10. Euclid preparation. Angular power spectra from discrete observations

Author: Euclid Collaboration, Tessore, N., Joachimi, B., Loureiro, A., Hall, A., Cañas-Herrera, G., Tutusaus, I., Jeffrey, N., Naidoo, K., McEwen, J. D., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Bardelli, S., Bernardeau, F., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Caillat, A., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Farrens, S., Faustini, F., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Keihänen, E., Kermiche, S., Kiessling, A., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marggraf, O., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Mohr, J. J., Moresco, M., Morin, B., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Seiffert, M., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Finelli, F., Gracia-Carpio, J., Matthew, S., Mauri, N., Pezzotta, A., Pöntinen, M., Scottez, V., Mancini, A. Spurio, Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Balaguera-Antolinez, A., Ballardini, M., Benielli, D., Blanchard, A., Blot, L., Böhringer, H., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Quevedo, B. Camacho, Cappi, A., Caro, F., Carvalho, C. S., Castro, T., Chambers, K. C., Cooray, A. R., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gasparetto, T., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Gutierrez, C. M., Hartley, W. G., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Kruk, S., Lacasa, F., Lattanzi, M., Brun, A. M. C. Le, Graet, J. Le, Legrand, L., Lesgourgues, J., Liaudat, T. I., Macias-Perez, J., Magliocchetti, M., Mannucci, F., Maoli, R., Martín-Fleitas, J., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Miluzio, M., Monaco, P., Montoro, A., Moretti, C., Morgante, G., Murray, C., Nadathur, S., Walton, Nicholas A., Patrizii, L., Popa, V., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Rollins, R. P., Sahlén, M., Sarpa, E., Schneider, A., Sereno, M., Simon, P., Tanidis, K., Tao, C., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., Vielzeuf, P., Brown, M. L., and Sellentin, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present the framework for measuring angular power spectra in the Euclid mission. The observables in galaxy surveys, such as galaxy clustering and cosmic shear, are not continuous fields, but discrete sets of data, obtained only at the positions of galaxies. We show how to compute the angular power spectra of such discrete data sets, without treating observations as maps of an underlying continuous field that is overlaid with a noise component. This formalism allows us to compute exact theoretical expectations for our measured spectra, under a number of assumptions that we track explicitly. In particular, we obtain exact expressions for the additive biases ("shot noise") in angular galaxy clustering and cosmic shear. For efficient practical computations, we introduce a spin-weighted spherical convolution with a well-defined convolution theorem, which allows us to apply exact theoretical predictions to finite-resolution maps, including HEALPix. When validating our methodology, we find that our measurements are biased by less than 1% of their statistical uncertainty in simulations of Euclid's first data release., Comment: 27 pages, 12 figures. Submitted to A&A. Code available at https://github.com/heracles-ec/heracles
Published: 2024

11. Euclid Preparation. Cosmic Dawn Survey: Data release 1 multiwavelength catalogues for Euclid Deep Field North and Euclid Deep Field Fornax

Author: Euclid Collaboration, Zalesky, L., McPartland, C. J. R., Weaver, J. R., Toft, S., Sanders, D. B., Mobasher, B., Suzuki, N., Szapudi, I., Valdes, I., Murphree, G., Chartab, N., Allen, N., Taamoli, S., Barrow, S. W. J., Ortiz, O. Chávez, Finkelstein, S. L., Gwyn, S., Sawicki, M., McCracken, H. J., Stern, D., Dannerbauer, H., Altieri, B., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Neissner, C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sapone, D., Scaramella, R., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Sefusatti, E., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., Gracia-Carpio, J., Mauri, N., Nucita, A. A., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Ballardini, M., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castro, T., Chambers, K. C., Chary, R., Contarini, S., Contini, T., Cooray, A. R., De Caro, B., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferrero, I., Finelli, F., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hall, A., Hartley, W. G., Hildebrandt, H., Hjorth, J., Huertas-Company, M., Ilbert, O., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Libet, G., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Moretti, C., Morgante, G., Walton, Nicholas A., Odier, J., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Scarlata, C., Schneider, A., Sereno, M., Silvestri, A., Simon, P., Mancini, A. Spurio, Stanford, S. A., Tao, C., Testera, G., Teyssier, R., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., and Zinchenko, I. A.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The Cosmic Dawn Survey (DAWN survey) provides multiwavelength (UV/optical to mid-IR) data across the combined 59 deg$^{2}$ of the Euclid Deep and Auxiliary fields (EDFs and EAFs). Here, the first public data release (DR1) from the DAWN survey is presented. DR1 catalogues are made available for a subset of the full DAWN survey that consists of two Euclid Deep fields: Euclid Deep Field North (EDF-N) and Euclid Deep Field Fornax (EDF-F). The DAWN survey DR1 catalogues do not include $Euclid$ data as they are not yet public for these fields. Nonetheless, each field has been covered by the ongoing Hawaii Twenty Square Degree Survey (H20), which includes imaging from CFHT MegaCam in the new $u$ filter and from Subaru Hyper Suprime-Cam (HSC) in the $griz$ filters. Each field is further covered by $Spitzer$/IRAC 3.6-4.5$\mu$m imaging spanning 10 deg$^{2}$ and reaching $\sim$25 mag AB (5$\sigma$). All present H20 imaging and all publicly available imaging from the aforementioned facilities are combined with the deep $Spitzer$/IRAC data to create source catalogues spanning a total area of 16.87 deg$^{2}$ in EDF-N and 2.85 deg$^{2}$ in EDF-F for this first release. Photometry is measured using The Farmer, a well-validated model-based photometry code. Photometric redshifts and stellar masses are computed using two independent codes for modeling spectral energy distributions: EAZY and LePhare. Photometric redshifts show good agreement with spectroscopic redshifts ($\sigma_{\rm NMAD} \sim 0.5, \eta < 8\%$ at $i < 25$). Number counts, photometric redshifts, and stellar masses are further validated in comparison to the COSMOS2020 catalogue. The DAWN survey DR1 catalogues are designed to be of immediate use in these two EDFs and will be continuously updated. Future data releases will provide catalogues of all EDFs and EAFs and include $Euclid$ data.
Published: 2024

12. Euclid preparation. The Cosmic Dawn Survey (DAWN) of the Euclid Deep and Auxiliary Fields

Author: Euclid Collaboration, McPartland, C. J. R., Zalesky, L., Weaver, J. R., Toft, S., Sanders, D. B., Mobasher, B., Suzuki, N., Szapudi, I., Valdes, I., Murphree, G., Chartab, N., Allen, N., Taamoli, S., Eisenhardt, P. R. M., Arnouts, S., Atek, H., Brinchmann, J., Castellano, M., Chary, R., Ortiz, O. Chávez, Cuby, J. -G., Finkelstein, S. L., Goto, T., Gwyn, S., Harikane, Y., Inoue, A. K., McCracken, H. J., Mohr, J. J., Oesch, P. A., Ouchi, M., Oguri, M., Rhodes, J., Rottgering, H. J. A., Sawicki, M., Scaramella, R., Scarlata, C., Silverman, J. D., Stern, D., Teplitz, H. I., Shuntov, M., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Aussel, H., Baccigalupi, C., Baldi, M., Bardelli, S., Bender, R., Bonino, D., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Fabricius, M., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., George, K., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Neissner, C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Surace, C., Tallada-Crespi, P., Tavagnacco, D., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Di Ferdinando, D., Farinelli, R., Gracia-Carpio, J., Mauri, N., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Ballardini, M., Bethermin, M., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Calabro, A., Cañas-Herrera, G., Cappi, A., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finelli, F., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Gregorio, A., Hall, A., Hartley, W. G., Hildebrandt, H., Hjorth, J., Huertas-Company, M., Ilbert, O., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Libet, G., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Monaco, P., Moretti, C., Morgante, G., Musi, P., Walton, Nicholas A., Odier, J., Patrizii, L., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Schneider, A., Sereno, M., Simon, P., Mancini, A. Spurio, Stanford, S. A., Tao, C., Testera, G., Teyssier, R., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., and Shankar, F.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Euclid will provide deep NIR imaging to $\sim$26.5 AB magnitude over $\sim$59 deg$^2$ in its deep and auxiliary fields. The Cosmic DAWN survey complements the deep Euclid data with matched depth multiwavelength imaging and spectroscopy in the UV--IR to provide consistently processed Euclid selected photometric catalogs, accurate photometric redshifts, and measurements of galaxy properties to a redshift of $z\sim 10$. In this paper, we present an overview of the survey, including the footprints of the survey fields, the existing and planned observations, and the primary science goals for the combined data set., Comment: 16 pages, 10 figures, submitted to A&A; Updated references; Updated author list
Published: 2024

13. Euclid preparation. Exploring the properties of proto-clusters in the Simulated Euclid Wide Survey

Author: Euclid Collaboration, Böhringer, H., Chon, G., Cucciati, O., Dannerbauer, H., Bolzonella, M., De Lucia, G., Cappi, A., Moscardini, L., Giocoli, C., Castignani, G., Hatch, N. A., Andreon, S., Bañados, E., Ettori, S., Fontanot, F., Gully, H., Hirschmann, M., Maturi, M., Mei, S., Pozzetti, L., Schlenker, T., Spinelli, M., Aghanim, N., Altieri, B., Auricchio, N., Baccigalupi, C., Baldi, M., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Farrens, S., Faustini, F., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillis, B., Gómez-Alvarez, P., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mellier, Y., Meneghetti, M., Meylan, G., Moresco, M., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Scodeggio, M., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Finelli, F., Gracia-Carpio, J., Matthew, S., Mauri, N., Pöntinen, M., Porciani, C., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Alvi, S., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Balaguera-Antolinez, A., Ballardini, M., Blanchard, A., Blot, L., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Caro, F., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., Costanzi, M., De Caro, B., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gasparetto, T., Gautard, V., Gaztanaga, E., Giacomini, F., Gianotti, F., Gonzalez, A. H., Gozaliasl, G., Gutierrez, C. M., Hall, A., Hartley, W. G., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Lesgourgues, J., Liaudat, T. I., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Miluzio, M., Monaco, P., Montoro, A., Mora, A., Moretti, C., Morgante, G., Walton, Nicholas A., Patrizii, L., Popa, V., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Schneider, A., Schultheis, M., Sereno, M., Shankar, F., Simon, P., Mancini, A. Spurio, Stadel, J., Stanford, S. A., Tanidis, K., Tao, C., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., and Verza, G.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Galaxy proto-clusters are receiving an increased interest since most of the processes shaping the structure of clusters of galaxies and their galaxy population are happening at early stages of their formation. The Euclid Survey will provide a unique opportunity to discover a large number of proto-clusters over a large fraction of the sky (14 500 square degrees). In this paper, we explore the expected observational properties of proto-clusters in the Euclid Wide Survey by means of theoretical models and simulations. We provide an overview of the predicted proto-cluster extent, galaxy density profiles, mass-richness relations, abundance, and sky-filling as a function of redshift. Useful analytical approximations for the functions of these properties are provided. The focus is on the redshift range z= 1.5 to 4. We discuss in particular the density contrast with which proto-clusters can be observed against the background in the galaxy distribution if photometric galaxy redshifts are used as supplied by the ESA Euclid mission together with the ground-based photometric surveys. We show that the obtainable detection significance is sufficient to find large numbers of interesting proto-cluster candidates. For quantitative studies, additional spectroscopic follow-up is required to confirm the proto-clusters and establish their richness., Comment: Submitted to Astronomy and Astrophysics, 24 pages, 28 figures
Published: 2024

14. Euclid preparation. LI. Forecasting the recovery of galaxy physical properties and their relations with template-fitting and machine-learning methods

Author: Euclid Collaboration, Enia, A., Bolzonella, M., Pozzetti, L., Humphrey, A., Cunha, P. A. C., Hartley, W. G., Dubath, F., Paltani, S., Lopez, X. Lopez, Quai, S., Bardelli, S., Bisigello, L., Cavuoti, S., De Lucia, G., Ginolfi, M., Grazian, A., Siudek, M., Tortora, C., Zamorani, G., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Castignani, G., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dupac, X., Dusini, S., Fabricius, M., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Fotopoulou, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillis, B., Giocoli, C., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Neissner, C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Pasian, F., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sapone, D., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Sefusatti, E., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Surace, C., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zucca, E., Biviano, A., Boucaud, A., Burigana, C., Calabrese, M., Vigo, J. A. Escartin, Gracia-Carpio, J., Mauri, N., Pezzotta, A., Pöntinen, M., Porciani, C., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Ballardini, M., Bergamini, P., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Contini, T., Cooray, A. R., Cucciati, O., Davini, S., De Caro, B., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Hall, A., Hemmati, S., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Graet, J. Le, Legrand, L., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Moretti, C., Morgante, G., Walton, Nicholas A., Patrizii, L., Popa, V., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Schneider, A., Schultheis, M., Sereno, M., Simon, P., Mancini, A. Spurio, Stanford, S. A., Tanidis, K., Tao, C., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., Zinchenko, I. A., Rodighiero, G., and Talia, M.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Euclid will collect an enormous amount of data during the mission's lifetime, observing billions of galaxies in the extragalactic sky. Along with traditional template-fitting methods, numerous machine learning algorithms have been presented for computing their photometric redshifts and physical parameters (PPs), requiring significantly less computing effort while producing equivalent performance measures. However, their performance is limited by the quality and amount of input information, to the point where the recovery of some well-established physical relationships between parameters might not be guaranteed. To forecast the reliability of Euclid photo-$z$s and PPs calculations, we produced two mock catalogs simulating Euclid photometry. We simulated the Euclid Wide Survey (EWS) and Euclid Deep Fields (EDF). We tested the performance of a template-fitting algorithm (Phosphoros) and four ML methods in recovering photo-$z$s, PPs (stellar masses and star formation rates), and the SFMS. To mimic the Euclid processing as closely as possible, the models were trained with Phosphoros-recovered labels. For the EWS, we found that the best results are achieved with a mixed labels approach, training the models with wide survey features and labels from the Phosphoros results on deeper photometry, that is, with the best possible set of labels for a given photometry. This imposes a prior, helping the models to better discern cases in degenerate regions of feature space, that is, when galaxies have similar magnitudes and colors but different redshifts and PPs, with performance metrics even better than those found with Phosphoros. We found no more than 3% performance degradation using a COSMOS-like reference sample or removing u band data, which will not be available until after data release DR1. The best results are obtained for the EDF, with appropriate recovery of photo-$z$, PPs, and the SFMS., Comment: 26 pages, 13 figures. Accepted for publication on A&A
Published: 2024

15. Euclid preparation. Sensitivity to non-standard particle dark matter model

Author: Euclid Collaboration, Lesgourgues, J., Schwagereit, J., Bucko, J., Parimbelli, G., Giri, S. K., Hervas-Peters, F., Schneider, A., Archidiacono, M., Pace, F., Sakr, Z., Amara, A., Amendola, L., Andreon, S., Auricchio, N., Aussel, H., Baccigalupi, C., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Ilić, S., Jahnke, K., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kubik, B., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Neissner, C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sánchez, A. G., Sapone, D., Sartoris, B., Scaramella, R., Schewtschenko, J. A., Schneider, P., Schrabback, T., Secroun, A., Sefusatti, E., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Fabbian, G., Farinelli, R., Gracia-Carpio, J., Mauri, N., Nucita, A. A., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Ballardini, M., Bertacca, D., Blot, L., Böhringer, H., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., Davini, S., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finelli, F., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Hjorth, J., Munñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Libet, G., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Moretti, C., Morgante, G., Nadathur, S., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Sereno, M., Simon, P., Mancini, A. Spurio, Tao, C., Tessore, N., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., and Verza, G.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Euclid mission of the European Space Agency will provide weak gravitational lensing and galaxy clustering surveys that can be used to constrain the standard cosmological model and its extensions, with an opportunity to test the properties of dark matter beyond the minimal cold dark matter paradigm. We present forecasts from the combination of these surveys on the parameters describing four interesting and representative non-minimal dark matter models: a mixture of cold and warm dark matter relics; unstable dark matter decaying either into massless or massive relics; and dark matter experiencing feeble interactions with relativistic relics. We model these scenarios at the level of the non-linear matter power spectrum using emulators trained on dedicated N-body simulations. We use a mock Euclid likelihood to fit mock data and infer error bars on dark matter parameters marginalised over other parameters. We find that the Euclid photometric probe (alone or in combination with CMB data from the Planck satellite) will be sensitive to the effect of each of the four dark matter models considered here. The improvement will be particularly spectacular for decaying and interacting dark matter models. With Euclid, the bounds on some dark matter parameters can improve by up to two orders of magnitude compared to current limits. We discuss the dependence of predicted uncertainties on different assumptions: inclusion of photometric galaxy clustering data, minimum angular scale taken into account, modelling of baryonic feedback effects. We conclude that the Euclid mission will be able to measure quantities related to the dark sector of particle physics with unprecedented sensitivity. This will provide important information for model building in high-energy physics. Any hint of a deviation from the minimal cold dark matter paradigm would have profound implications for cosmology and particle physics., Comment: 31 pages, 21 figures
Published: 2024

16. Euclid preparation. Observational expectations for redshift z<7 active galactic nuclei in the Euclid Wide and Deep surveys

Author: Euclid Collaboration, Selwood, M., Fotopoulou, S., Bremer, M. N., Bisigello, L., Landt, H., Bañados, E., Zamorani, G., Shankar, F., Stern, D., Lusso, E., Spinoglio, L., Allevato, V., Ricci, F., Feltre, A., Mannucci, F., Salvato, M., Bowler, R. A. A., Mignoli, M., Vergani, D., La Franca, F., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Holliman, M. S., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Rix, Hans-Walter, Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Scaramella, R., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zucca, E., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Colodro-Conde, C., De Lucia, G., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., George, K., Gracia-Carpio, J., Martinelli, M., Mauri, N., Neissner, C., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Baccigalupi, C., Ballardini, M., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Contarini, S., Contini, T., Cooray, A. R., Cucciati, O., Davini, S., De Caro, B., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferrero, I., Finelli, F., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hall, A., Hildebrandt, H., Hjorth, J., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Libet, G., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Moretti, C., Morgante, G., Nadathur, S., Nicastro, L., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Sánchez, A. G., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Steinwagner, J., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Verza, G., Weaver, J. R., and Zinchenko, I. A.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We forecast the expected population of active galactic nuclei (AGN) observable in the Euclid Wide Survey (EWS) and Euclid Deep Survey (EDS). Starting from an X-ray luminosity function (XLF) we generate volume-limited samples of the AGN expected in the survey footprints. Each AGN is assigned an SED appropriate for its X-ray luminosity and redshift, with perturbations sampled from empirical distributions. The photometric detectability of each AGN is assessed via mock observation of the assigned SED. We estimate 40 million AGN will be detectable in at least one band in the EWS and 0.24 million in the EDS, corresponding to surface densities of 2.8$\times$10$^{3}$ deg$^{-2}$ and 4.7$\times$10$^{3}$ deg$^{-2}$. Employing colour selection criteria on our simulated data we select a sample of 4.8$\times$10$^{6}$ (331 deg$^{-2}$) AGN in the EWS and 1.7$\times$10$^{4}$ (346 deg$^{-2}$) in the EDS, amounting to 10% and 8% of the AGN detectable in the EWS and EDS. Including ancillary Rubin/LSST bands improves the completeness and purity of AGN selection. These data roughly double the total number of selected AGN to comprise 21% and 15% of the detectable AGN in the EWS and EDS. The total expected sample of colour-selected AGN contains 6.0$\times$10$^{6}$ (74%) unobscured AGN and 2.1$\times$10$^{6}$ (26%) obscured AGN, covering $0.02 \leq z \lesssim 5.2$ and $43 \leq \log_{10} (L_{bol} / erg s^{-1}) \leq 47$. With this simple colour selection, expected surface densities are already comparable to the yield of modern X-ray and mid-infrared surveys of similar area. The relative uncertainty on our expectation for detectable AGN is 6.7% for the EWS and 12.5% for the EDS, driven by the uncertainty of the XLF., Comment: 36 pages, 21 figures, submitted to A&A
Published: 2024

17. Euclid preparation. Detecting globular clusters in the Euclid survey

Author: Euclid Collaboration, Voggel, K., Lançon, A., Saifollahi, T., Larsen, S. S., Cantiello, M., Rejkuba, M., Cuillandre, J. -C., Hudelot, P., Nucita, A. A., Urbano, M., Romelli, E., Raj, M. A., Schirmer, M., Tortora, C., Abdurro'uf, Annibali, F., Baes, M., Boldrini, P., Cabanac, R., Carollo, D., Conselice, C. J., Duc, P. -A., Ferguson, A. M. N., Hunt, L. K., Knapen, J. H., Lonare, P., Marleau, F. R., Poulain, M., Sánchez-Janssen, R., Sola, E., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carlberg, R. G., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kohley, R., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Nichol, R. C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Scaramella, R., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Calabrese, M., Colodro-Conde, C., De Lucia, G., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., George, K., Gracia-Carpio, J., Liebing, P., Martinelli, M., Mauri, N., Neissner, C., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Borlaff, A. S., Bruton, S., Calabro, A., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., De Caro, B., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrero, I., Finelli, F., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hall, A., Hildebrandt, H., Hjorth, J., Ilbert, O., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Libet, G., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Moretti, C., Morgante, G., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Steinwagner, J., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Vergani, D., Verza, G., Zinchenko, I. A., Mamon, G. A., and Scott, D.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Extragalactic globular clusters (EGCs) are an abundant and powerful tracer of galaxy dynamics and formation, and their own formation and evolution is also a matter of extensive debate. The compact nature of globular clusters means that they are hard to spatially resolve and thus study outside the Local Group. In this work we have examined how well EGCs will be detectable in images from the Euclid telescope, using both simulated pre-launch images and the first early-release observations of the Fornax galaxy cluster. The Euclid Wide Survey will provide high-spatial resolution VIS imaging in the broad IE band as well as near-infrared photometry (YE, JE, and HE). We estimate that the galaxies within 100 Mpc in the footprint of the Euclid survey host around 830 000 EGCs of which about 350 000 are within the survey's detection limits. For about half of these EGCs, three infrared colours will be available as well. For any galaxy within 50Mpc the brighter half of its GC luminosity function will be detectable by the Euclid Wide Survey. The detectability of EGCs is mainly driven by the residual surface brightness of their host galaxy. We find that an automated machine-learning EGC-classification method based on real Euclid data of the Fornax galaxy cluster provides an efficient method to generate high purity and high completeness GC candidate catalogues. We confirm that EGCs are spatially resolved compared to pure point sources in VIS images of Fornax. Our analysis of both simulated and first on-sky data show that Euclid will increase the number of GCs accessible with high-resolution imaging substantially compared to previous surveys, and will permit the study of GCs in the outskirts of their hosts. Euclid is unique in enabling systematic studies of EGCs in a spatially unbiased and homogeneous manner and is primed to improve our understanding of many understudied aspects of GC astrophysics., Comment: Submitted to A&A
Published: 2024

18. Euclid. V. The Flagship galaxy mock catalogue: a comprehensive simulation for the Euclid mission

Author: Euclid Collaboration, Castander, F. J., Fosalba, P., Stadel, J., Potter, D., Carretero, J., Tallada-Crespí, P., Pozzetti, L., Bolzonella, M., Mamon, G. A., Blot, L., Hoffmann, K., Huertas-Company, M., Monaco, P., Gonzalez, E. J., De Lucia, G., Scarlata, C., Breton, M. -A., Linke, L., Viglione, C., Li, S. -S., Zhai, Z., Baghkhani, Z., Pardede, K., Neissner, C., Teyssier, R., Crocce, M., Tutusaus, I., Miller, L., Congedo, G., Biviano, A., Hirschmann, M., Pezzotta, A., Aussel, H., Hoekstra, H., Kitching, T., Percival, W. J., Guzzo, L., Mellier, Y., Oesch, P. A., Bowler, R. A. A., Bruton, S., Allevato, V., Gonzalez-Perez, V., Manera, M., Avila, S., Kovács, A., Aghanim, N., Altieri, B., Amara, A., Amendola, L., Andreon, S., Auricchio, N., Baldi, M., Balestra, A., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Fourmanoit, N., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Granett, B. R., Grazian, A., Grupp, F., Haugan, S. V. H., Holliman, M. S., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kohley, R., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Laureijs, R., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Masters, D. C., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Mohr, J. J., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Nichol, R. C., Niemi, S. -M., Padilla, C., Paech, K., Paltani, S., Pasian, F., Peacock, J. A., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rosset, C., Rossetti, E., Saglia, R., Sapone, D., Schirmer, M., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tsyganov, A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zerbi, F. M., Zoubian, J., Zucca, E., Baccigalupi, C., Bernardeau, F., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Casenove, P., Castignani, G., Colodro-Conde, C., Di Ferdinando, D., Vigo, J. A. Escartin, Fabbian, G., Finelli, F., Gracia-Carpio, J., Ilić, S., Liebing, P., Marcin, S., Martinelli, M., Matthew, S., Mauri, N., Pöntinen, M., Porciani, C., Sakr, Z., Scottez, V., Sefusatti, E., Steinwagner, J., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Aubourg, E., Balaguera-Antolinez, A., Ballardini, M., Bertacca, D., Bethermin, M., Blanchard, A., Böhringer, H., Borgani, S., Bouvard, T., Cabanac, R., Calabro, A., Quevedo, B. Camacho, Canas-Herrera, G., Cappi, A., Caro, F., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Contini, T., Cooray, A. R., Costanzi, M., Cucciati, O., Davini, S., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ezziati, M., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gasparetto, T., Gaztanaga, E., Giacomini, F., Gianotti, F., Gonzalez, A. H., Gozaliasl, G., Hall, A., Hartley, W. G., Hildebrandt, H., Hjorth, J., Holland, A. D., Ilbert, O., Joudaki, S., Jullo, E., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Graet, J. Le, Legrand, L., Lesgourgues, J., Liaudat, T. I., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Migliaccio, M., Miluzio, M., Mora, A., Moretti, C., Morgante, G., Nadathur, S., Nicastro, L., Walton, Nicholas A., Oguri, M., Patrizii, L., Popa, V., Pourtsidou, A., Reimberg, P., Risso, I., Rocci, P. -F., Rollins, R. P., Rusholme, B., Sahlén, M., Sánchez, A. G., Schaye, J., Schewtschenko, J. A., Schneider, A., Schultheis, M., Sereno, M., Shankar, F., Shulevski, A., Silvestri, A., Simon, P., Mancini, A. Spurio, Stanford, S. A., Tanidis, K., Tao, C., Tessore, N., Testera, G., Tewes, M., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Vernizzi, F., Verza, G., Vielzeuf, P., Weaver, J. R., Zalesky, L., Dimauro, P., Duc, P. -A., Fang, Y., Ferguson, A. M. N., Gutierrez, C. M., Kova{č}ić, I., Kruk, S., Brun, A. M. C. Le, Montoro, A., Murray, C., Pagano, L., Paoletti, D., Sarpa, E., Viitanen, A., Martín-Fleitas, J., and Yung, L. Y. A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present the Flagship galaxy mock, a simulated catalogue of billions of galaxies designed to support the scientific exploitation of the Euclid mission. Euclid is a medium-class mission of the European Space Agency optimised to determine the properties of dark matter and dark energy on the largest scales of the Universe. It probes structure formation over more than 10 billion years primarily from the combination of weak gravitational lensing and galaxy clustering data. The breath of Euclid's data will also foster a wide variety of scientific analyses. The Flagship simulation was developed to provide a realistic approximation to the galaxies that will be observed by Euclid and used in its scientific analyses. We ran a state-of-the-art N-body simulation with four trillion particles, producing a lightcone on the fly. From the dark matter particles, we produced a catalogue of 16 billion haloes in one octant of the sky in the lightcone up to redshift z=3. We then populated these haloes with mock galaxies using a halo occupation distribution and abundance matching approach, calibrating the free parameters of the galaxy mock against observed correlations and other basic galaxy properties. Modelled galaxy properties include luminosity and flux in several bands, redshifts, positions and velocities, spectral energy distributions, shapes and sizes, stellar masses, star formation rates, metallicities, emission line fluxes, and lensing properties. We selected a final sample of 3.4 billion galaxies with a magnitude cut of H_E<26, where we are complete. We have performed a comprehensive set of validation tests to check the similarity to observational data and theoretical models. In particular, our catalogue is able to closely reproduce the main characteristics of the weak lensing and galaxy clustering samples to be used in the mission's main cosmological analysis. (abridged), Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations
Published: 2024

19. Euclid. IV. The NISP Calibration Unit

Author: Euclid Collaboration, Hormuth, F., Jahnke, K., Schirmer, M., Lee, C. G. -Y., Scott, T., Barbier, R., Ferriol, S., Gillard, W., Grupp, F., Holmes, R., Holmes, W., Kubik, B., Macias-Perez, J., Laurent, M., Marpaud, J., Marton, M., Medinaceli, E., Morgante, G., Toledo-Moreo, R., Trifoglio, M., Rix, Hans-Walter, Secroun, A., Seiffert, M., Stassi, P., Wachter, S., Gutierrez, C. M., Vescovi, C., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Balestra, A., Bardelli, S., Battaglia, P., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, R., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Dinis, J., Douspis, M., Dubath, F., Ducret, F., Dupac, X., Dusini, S., Fabricius, M., Farina, M., Farrens, S., Faustini, F., Fotopoulou, S., Fourmanoit, N., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., George, K., Gillis, B., Giocoli, C., Grazian, A., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Hook, I., Hornstrup, A., Hudelot, P., Jhabvala, M., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kümmel, M., Kunz, M., Kurki-Suonio, H., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Mohr, J. J., Moresco, M., Morris, P. W., Moscardini, L., Munari, E., Nakajima, R., Neissner, C., Nichol, R. C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paech, K., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Rusholme, B., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Sauvage, M., Schewtschenko, J. A., Schneider, P., Schrabback, T., Sefusatti, E., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Smadja, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., Tereno, I., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zerbi, F. M., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., Gracia-Carpio, J., Kazandjian, M. V., Mauri, N., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Aubourg, E., Ballardini, M., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Borlaff, A. S., Borsato, E., Bruton, S., Cabanac, R., Calabro, A., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Casenove, P., Castro, T., Chambers, K. C., Charles, Y., Contarini, S., Cooray, A. R., Cucciati, O., Davini, S., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finelli, F., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hall, A., Hartley, W. G., Hildebrandt, H., Hjorth, J., Huertas-Company, M., Ilbert, O., Jacobson, J., Muñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Laudisio, F., Legrand, L., Libet, G., Loureiro, A., Maggio, G., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Miluzio, M., Moretti, C., Nadathur, S., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Risso, I., Rocci, P. -F., Rollins, R. P., Sahlén, M., Scarlata, C., Schneider, A., Schultheis, M., Sereno, M., Shulevski, A., Silvestri, A., Simon, P., Mancini, A. Spurio, Stadel, J., Tao, C., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., Zalesky, L., Archidiacono, M., Atrio-Barandela, F., Bouvard, T., Caro, F., Dimauro, P., Fang, Y., Ferguson, A. M. N., Finoguenov, A., Gasparetto, T., Brun, A. M. C. Le, Graet, J. Le, Liaudat, T. I., Montoro, A., Murray, C., Oguri, M., Pagano, L., Paoletti, D., Sarpa, E., Tanidis, K., Vernizzi, F., Viitanen, A., Kova{č}ić, I., Lesgourgues, J., Martín-Fleitas, J., and Mora, A.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The near-infrared calibration unit (NI-CU) on board Euclid's Near-Infrared Spectrometer and Photometer (NISP) is the first astronomical calibration lamp based on light-emitting diodes (LEDs) to be operated in space. Euclid is a mission in ESA's Cosmic Vision 2015-2025 framework, to explore the dark universe and provide a next-level characterisation of the nature of gravitation, dark matter, and dark energy. Calibrating photometric and spectrometric measurements of galaxies to better than 1.5% accuracy in a survey homogeneously mapping ~14000 deg^2 of extragalactic sky requires a very detailed characterisation of near-infrared (NIR) detector properties, as well their constant monitoring in flight. To cover two of the main contributions - relative pixel-to-pixel sensitivity and non-linearity characteristics - as well as support other calibration activities, NI-CU was designed to provide spatially approximately homogeneous (<12% variations) and temporally stable illumination (0.1%-0.2% over 1200s) over the NISP detector plane, with minimal power consumption and energy dissipation. NI-CU is covers the spectral range ~[900,1900] nm - at cryo-operating temperature - at 5 fixed independent wavelengths to capture wavelength-dependent behaviour of the detectors, with fluence over a dynamic range of >=100 from ~15 ph s^-1 pixel^-1 to >1500 ph s^-1 pixel^-1. For this functionality, NI-CU is based on LEDs. We describe the rationale behind the decision and design process, describe the challenges in sourcing the right LEDs, as well as the qualification process and lessons learned. We also provide a description of the completed NI-CU, its capabilities and performance as well as its limits. NI-CU has been integrated into NISP and the Euclid satellite, and since Euclid's launch in July 2023 has started supporting survey operations., Comment: Paper accepted for publication in A&A as part of the special issue 'Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations
Published: 2024

20. Euclid. III. The NISP Instrument

Author: Euclid Collaboration, Jahnke, K., Gillard, W., Schirmer, M., Ealet, A., Maciaszek, T., Prieto, E., Barbier, R., Bonoli, C., Corcione, L., Dusini, S., Grupp, F., Hormuth, F., Ligori, S., Martin, L., Morgante, G., Padilla, C., Toledo-Moreo, R., Trifoglio, M., Valenziano, L., Bender, R., Castander, F. J., Garilli, B., Lilje, P. B., Rix, H. -W., Auricchio, N., Balestra, A., Barriere, J. -C., Battaglia, P., Berthe, M., Bodendorf, C., Boenke, T., Bon, W., Bonnefoi, A., Caillat, A., Capobianco, V., Carle, M., Casas, R., Cho, H., Costille, A., Ducret, F., Ferriol, S., Franceschi, E., Gimenez, J. -L., Holmes, W., Hornstrup, A., Jhabvala, M., Kohley, R., Kubik, B., Laureijs, R., Mignant, D. Le, Lloro, I., Medinaceli, E., Mellier, Y., Polenta, G., Racca, G. D., Renzi, A., Salvignol, J. -C., Secroun, A., Seidel, G., Seiffert, M., Sirignano, C., Sirri, G., Strada, P., Smadja, G., Stanco, L., Wachter, S., Anselmi, S., Borsato, E., Caillat, L., Cogato, F., Colodro-Conde, C., Crouzet, P. -E., Conforti, V., D'Alessandro, M., Copin, Y., Cuillandre, J. -C., Davies, J. E., Davini, S., Derosa, A., Diaz, J. J., Di Domizio, S., Di Ferdinando, D., Farinelli, R., Ferrari, A. G., Fornari, F., Gabarra, L., Gutierrez, C. M., Giacomini, F., Lagier, P., Gianotti, F., Krause, O., Madrid, F., Laudisio, F., Macias-Perez, J., Naletto, G., Niclas, M., Marpaud, J., Mauri, N., da Silva, R., Passalacqua, F., Paterson, K., Patrizii, L., Risso, I., Solheim, B. G. B., Scodeggio, M., Stassi, P., Steinwagner, J., Tenti, M., Testera, G., Travaglini, R., Tosi, S., Troja, A., Tubio, O., Valieri, C., Vescovi, C., Ventura, S., Aghanim, N., Altieri, B., Amara, A., Amiaux, J., Andreon, S., Aussel, H., Baldi, M., Bardelli, S., Basset, A., Bonchi, A., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Chabaud, P. -Y., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Courbin, F., Courtois, H. M., Cropper, M., Cuby, J. -G., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Fabricius, M., Farina, M., Farrens, S., Faustini, F., Fosalba, P., Fotopoulou, S., Fourmanoit, N., Frailis, M., Franzetti, P., Galeotta, S., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Granett, B. R., Grazian, A., Guzzo, L., Hailey, M., Haugan, S. V. H., Hoar, J., Hoekstra, H., Hook, I., Hudelot, P., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Lindholm, V., Alvarez, J. Lorenzo, Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martignac, J., Martinet, N., Marulli, F., Massey, R., Masters, D. C., Maurogordato, S., McCracken, H. J., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Mohr, J. J., Moresco, M., Moscardini, L., Nakajima, R., Nichol, R. C., Niemi, S. -M., Nutma, T., Paech, K., Paltani, S., Pasian, F., Peacock, J. A., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Refregier, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rosset, C., Rossetti, E., Rottgering, H. J. A., Saglia, R., Sapone, D., Sauvage, M., Scaramella, R., Schneider, P., Schrabback, T., Serrano, S., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., Tereno, I., Torradeflot, F., Tutusaus, I., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Vibert, D., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zerbi, F. M., Zoubian, J., Zucca, E., Appleton, P. N., Baccigalupi, C., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Casenove, P., Crocce, M., De Lucia, G., Vigo, J. A. Escartin, Fabbian, G., Finelli, F., George, K., Gracia-Carpio, J., Ilić, S., Liebing, P., Liu, C., Mainetti, G., Marcin, S., Martinelli, M., Morris, P. W., Neissner, C., Pezzotta, A., Pöntinen, M., Porciani, C., Sakr, Z., Scottez, V., Sefusatti, E., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Aubourg, E., Ballardini, M., Bertacca, D., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Calabro, A., Calderone, G., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Charles, Y., Chary, R., Colbert, J., Contarini, S., Contini, T., Cooray, A. R., Costanzi, M., Cucciati, O., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Dole, H., Escoffier, S., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Gozaliasl, G., Gregorio, A., Hall, A., Hartley, W. G., Hemmati, S., Hildebrandt, H., Hjorth, J., Hosseini, S., Huertas-Company, M., Ilbert, O., Jacobson, J., Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Lacasa, F., Brun, V. Le, Graet, J. Le, Legrand, L., Libet, G., Liu, S. J., Loureiro, A., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., McPartland, C. J. R., Metcalf, R. B., Migliaccio, M., Miluzio, M., Monaco, P., Moretti, C., Nadathur, S., Nicastro, L., Walton, Nicholas A., Odier, J., Oguri, M., Popa, V., Potter, D., Pourtsidou, A., Rocci, P. -F., Rollins, R. P., Rusholme, B., Sahlén, M., Sánchez, A. G., Scarlata, C., Schaye, J., Schewtschenko, J. A., Schneider, A., Schultheis, M., Sereno, M., Shankar, F., Shulevski, A., Sikkema, G., Silvestri, A., Simon, P., Mancini, A. Spurio, Stadel, J., Stanford, S. A., Tanidis, K., Tao, C., Tessore, N., Teyssier, R., Toft, S., Tucci, M., Valiviita, J., Vergani, D., Vernizzi, F., Verza, G., Vielzeuf, P., Weaver, J. R., Zalesky, L., Zinchenko, I. A., Archidiacono, M., Atrio-Barandela, F., Bennett, C. L., Bouvard, T., Caro, F., Conseil, S., Dimauro, P., Duc, P. -A., Fang, Y., Ferguson, A. M. N., Gasparetto, T., Kova{č}ić, I., Kruk, S., Brun, A. M. C. Le, Liaudat, T. I., Montoro, A., Mora, A., Murray, C., Pagano, L., Paoletti, D., Radovich, M., Sarpa, E., Tommasi, E., Viitanen, A., Lesgourgues, J., Levi, M. E., and Martín-Fleitas, J.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The Near-Infrared Spectrometer and Photometer (NISP) on board the Euclid satellite provides multiband photometry and R>=450 slitless grism spectroscopy in the 950-2020nm wavelength range. In this reference article we illuminate the background of NISP's functional and calibration requirements, describe the instrument's integral components, and provide all its key properties. We also sketch the processes needed to understand how NISP operates and is calibrated, and its technical potentials and limitations. Links to articles providing more details and technical background are included. NISP's 16 HAWAII-2RG (H2RG) detectors with a plate scale of 0.3" pix^-1 deliver a field-of-view of 0.57deg^2. In photo mode, NISP reaches a limiting magnitude of ~24.5AB mag in three photometric exposures of about 100s exposure time, for point sources and with a signal-to-noise ratio (SNR) of 5. For spectroscopy, NISP's point-source sensitivity is a SNR = 3.5 detection of an emission line with flux ~2x10^-16erg/s/cm^2 integrated over two resolution elements of 13.4A, in 3x560s grism exposures at 1.6 mu (redshifted Ha). Our calibration includes on-ground and in-flight characterisation and monitoring of detector baseline, dark current, non-linearity, and sensitivity, to guarantee a relative photometric accuracy of better than 1.5%, and relative spectrophotometry to better than 0.7%. The wavelength calibration must be better than 5A. NISP is the state-of-the-art instrument in the NIR for all science beyond small areas available from HST and JWST - and an enormous advance due to its combination of field size and high throughput of telescope and instrument. During Euclid's 6-year survey covering 14000 deg^2 of extragalactic sky, NISP will be the backbone for determining distances of more than a billion galaxies. Its NIR data will become a rich reference imaging and spectroscopy data set for the coming decades., Comment: Paper submitted as part of the A&A special issue 'Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations
Published: 2024

21. Euclid. I. Overview of the Euclid mission

Author: Euclid Collaboration, Mellier, Y., Abdurro'uf, Barroso, J. A. Acevedo, Achúcarro, A., Adamek, J., Adam, R., Addison, G. E., Aghanim, N., Aguena, M., Ajani, V., Akrami, Y., Al-Bahlawan, A., Alavi, A., Albuquerque, I. S., Alestas, G., Alguero, G., Allaoui, A., Allen, S. W., Allevato, V., Alonso-Tetilla, A. V., Altieri, B., Alvarez-Candal, A., Alvi, S., Amara, A., Amendola, L., Amiaux, J., Andika, I. T., Andreon, S., Andrews, A., Angora, G., Angulo, R. E., Annibali, F., Anselmi, A., Anselmi, S., Arcari, S., Archidiacono, M., Aricò, G., Arnaud, M., Arnouts, S., Asgari, M., Asorey, J., Atayde, L., Atek, H., Atrio-Barandela, F., Aubert, M., Aubourg, E., Auphan, T., Auricchio, N., Aussel, B., Aussel, H., Avelino, P. P., Avgoustidis, A., Avila, S., Awan, S., Azzollini, R., Baccigalupi, C., Bachelet, E., Bacon, D., Baes, M., Bagley, M. B., Bahr-Kalus, B., Balaguera-Antolinez, A., Balbinot, E., Balcells, M., Baldi, M., Baldry, I., Balestra, A., Ballardini, M., Ballester, O., Balogh, M., Bañados, E., Barbier, R., Bardelli, S., Baron, M., Barreiro, T., Barrena, R., Barriere, J. -C., Barros, B. J., Barthelemy, A., Bartolo, N., Basset, A., Battaglia, P., Battisti, A. J., Baugh, C. M., Baumont, L., Bazzanini, L., Beaulieu, J. -P., Beckmann, V., Belikov, A. N., Bel, J., Bellagamba, F., Bella, M., Bellini, E., Benabed, K., Bender, R., Benevento, G., Bennett, C. L., Benson, K., Bergamini, P., Bermejo-Climent, J. R., Bernardeau, F., Bertacca, D., Berthe, M., Berthier, J., Bethermin, M., Beutler, F., Bevillon, C., Bhargava, S., Bhatawdekar, R., Bianchi, D., Bisigello, L., Biviano, A., Blake, R. P., Blanchard, A., Blazek, J., Blot, L., Bosco, A., Bodendorf, C., Boenke, T., Böhringer, H., Boldrini, P., Bolzonella, M., Bonchi, A., Bonici, M., Bonino, D., Bonino, L., Bonvin, C., Bon, W., Booth, J. T., Borgani, S., Borlaff, A. S., Borsato, E., Bose, B., Botticella, M. T., Boucaud, A., Bouche, F., Boucher, J. S., Boutigny, D., Bouvard, T., Bouwens, R., Bouy, H., Bowler, R. A. A., Bozza, V., Bozzo, E., Branchini, E., Brando, G., Brau-Nogue, S., Brekke, P., Bremer, M. N., Brescia, M., Breton, M. -A., Brinchmann, J., Brinckmann, T., Brockley-Blatt, C., Brodwin, M., Brouard, L., Brown, M. L., Bruton, S., Bucko, J., Buddelmeijer, H., Buenadicha, G., Buitrago, F., Burger, P., Burigana, C., Busillo, V., Busonero, D., Cabanac, R., Cabayol-Garcia, L., Cagliari, M. S., Caillat, A., Caillat, L., Calabrese, M., Calabro, A., Calderone, G., Calura, F., Quevedo, B. Camacho, Camera, S., Campos, L., Canas-Herrera, G., Candini, G. P., Cantiello, M., Capobianco, V., Cappellaro, E., Cappelluti, N., Cappi, A., Caputi, K. I., Cara, C., Carbone, C., Cardone, V. F., Carella, E., Carlberg, R. G., Carle, M., Carminati, L., Caro, F., Carrasco, J. M., Carretero, J., Carrilho, P., Duque, J. Carron, Carry, B., Carvalho, A., Carvalho, C. S., Casas, R., Casas, S., Casenove, P., Casey, C. M., Cassata, P., Castander, F. J., Castelao, D., Castellano, M., Castiblanco, L., Castignani, G., Castro, T., Cavet, C., Cavuoti, S., Chabaud, P. -Y., Chambers, K. C., Charles, Y., Charlot, S., Chartab, N., Chary, R., Chaumeil, F., Cho, H., Chon, G., Ciancetta, E., Ciliegi, P., Cimatti, A., Cimino, M., Cioni, M. -R. L., Claydon, R., Cleland, C., Clément, B., Clements, D. L., Clerc, N., Clesse, S., Codis, S., Cogato, F., Colbert, J., Cole, R. E., Coles, P., Collett, T. E., Collins, R. S., Colodro-Conde, C., Colombo, C., Combes, F., Conforti, V., Congedo, G., Conseil, S., Conselice, C. J., Contarini, S., Contini, T., Conversi, L., Cooray, A. R., Copin, Y., Corasaniti, P. -S., Corcho-Caballero, P., Corcione, L., Cordes, O., Corpace, O., Correnti, M., Costanzi, M., Costille, A., Courbin, F., Mifsud, L. Courcoult, Courtois, H. M., Cousinou, M. -C., Covone, G., Cowell, T., Cragg, C., Cresci, G., Cristiani, S., Crocce, M., Cropper, M., Crouzet, P. E, Csizi, B., Cuby, J. -G., Cucchetti, E., Cucciati, O., Cuillandre, J. -C., Cunha, P. A. C., Cuozzo, V., Daddi, E., D'Addona, M., Dafonte, C., Dagoneau, N., Dalessandro, E., Dalton, G. B., D'Amico, G., Dannerbauer, H., Danto, P., Das, I., Da Silva, A., da Silva, R., Doumerg, W. d'Assignies, Daste, G., Davies, J. E., Davini, S., Dayal, P., de Boer, T., Decarli, R., De Caro, B., Degaudenzi, H., Degni, G., de Jong, J. T. A., de la Bella, L. F., de la Torre, S., Delhaise, F., Delley, D., Delucchi, G., De Lucia, G., Denniston, J., De Paolis, F., De Petris, M., Derosa, A., Desai, S., Desjacques, V., Despali, G., Desprez, G., De Vicente-Albendea, J., Deville, Y., Dias, J. D. F., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Diego, J. M., Di Ferdinando, D., Di Giorgio, A. M., Dimauro, P., Dinis, J., Dolag, K., Dolding, C., Dole, H., Sánchez, H. Domínguez, Doré, O., Dournac, F., Douspis, M., Dreihahn, H., Droge, B., Dryer, B., Dubath, F., Duc, P. -A., Ducret, F., Duffy, C., Dufresne, F., Duncan, C. A. J., Dupac, X., Duret, V., Durrer, R., Durret, F., Dusini, S., Ealet, A., Eggemeier, A., Eisenhardt, P. R. M., Elbaz, D., Elkhashab, M. Y., Ellien, A., Endicott, J., Enia, A., Erben, T., Vigo, J. A. Escartin, Escoffier, S., Sanz, I. Escudero, Essert, J., Ettori, S., Ezziati, M., Fabbian, G., Fabricius, M., Fang, Y., Farina, A., Farina, M., Farinelli, R., Farrens, S., Faustini, F., Feltre, A., Ferguson, A. M. N., Ferrando, P., Ferrari, A. G., Ferré-Mateu, A., Ferreira, P. G., Ferreras, I., Ferrero, I., Ferriol, S., Ferruit, P., Filleul, D., Finelli, F., Finkelstein, S. L., Finoguenov, A., Fiorini, B., Flentge, F., Focardi, P., Fonseca, J., Fontana, A., Fontanot, F., Fornari, F., Fosalba, P., Fossati, M., Fotopoulou, S., Fouchez, D., Fourmanoit, N., Frailis, M., Fraix-Burnet, D., Franceschi, E., Franco, A., Franzetti, P., Freihoefer, J., Frenk, C. . S., Frittoli, G., Frugier, P. -A., Frusciante, N., Fumagalli, A., Fumagalli, M., Fumana, M., Fu, Y., Gabarra, L., Galeotta, S., Galluccio, L., Ganga, K., Gao, H., García-Bellido, J., Garcia, K., Gardner, J. P., Garilli, B., Gaspar-Venancio, L. -M., Gasparetto, T., Gautard, V., Gavazzi, R., Gaztanaga, E., Genolet, L., Santos, R. Genova, Gentile, F., George, K., Gerbino, M., Ghaffari, Z., Giacomini, F., Gianotti, F., Gibb, G. P. S., Gillard, W., Gillis, B., Ginolfi, M., Giocoli, C., Girardi, M., Giri, S. K., Goh, L. W. K., Gómez-Alvarez, P., Gonzalez-Perez, V., Gonzalez, A. H., Gonzalez, E. J., Gonzalez, J. C., Beauchamps, S. Gouyou, Gozaliasl, G., Gracia-Carpio, J., Grandis, S., Granett, B. R., Granvik, M., Grazian, A., Gregorio, A., Grenet, C., Grillo, C., Grupp, F., Gruppioni, C., Gruppuso, A., Guerbuez, C., Guerrini, S., Guidi, M., Guillard, P., Gutierrez, C. M., Guttridge, P., Guzzo, L., Gwyn, S., Haapala, J., Haase, J., Haddow, C. R., Hailey, M., Hall, A., Hall, D., Hamaus, N., Haridasu, B. S., Harnois-Déraps, J., Harper, C., Hartley, W. G., Hasinger, G., Hassani, F., Hatch, N. A., Haugan, S. V. H., Häußler, B., Heavens, A., Heisenberg, L., Helmi, A., Helou, G., Hemmati, S., Henares, K., Herent, O., Hernández-Monteagudo, C., Heuberger, T., Hewett, P. C., Heydenreich, S., Hildebrandt, H., Hirschmann, M., Hjorth, J., Hoar, J., Hoekstra, H., Holland, A. D., Holliman, M. S., Holmes, W., Hook, I., Horeau, B., Hormuth, F., Hornstrup, A., Hosseini, S., Hu, D., Hudelot, P., Hudson, M. J., Huertas-Company, M., Huff, E. M., Hughes, A. C. N., Humphrey, A., Hunt, L. K., Huynh, D. D., Ibata, R., Ichikawa, K., Iglesias-Groth, S., Ilbert, O., Ilić, S., Ingoglia, L., Iodice, E., Israel, H., Israelsson, U. E., Izzo, L., Jablonka, P., Jackson, N., Jacobson, J., Jafariyazani, M., Jahnke, K., Jain, B., Jansen, H., Jarvis, M. J., Jasche, J., Jauzac, M., Jeffrey, N., Jhabvala, M., Jimenez-Teja, Y., Muñoz, A. Jimenez, Joachimi, B., Johansson, P. H., Joudaki, S., Jullo, E., Kajava, J. J. E., Kang, Y., Kannawadi, A., Kansal, V., Karagiannis, D., Kärcher, M., Kashlinsky, A., Kazandjian, M. V., Keck, F., Keihänen, E., Kerins, E., Kermiche, S., Khalil, A., Kiessling, A., Kiiveri, K., Kilbinger, M., Kim, J., King, R., Kirkpatrick, C. C., Kitching, T., Kluge, M., Knabenhans, M., Knapen, J. H., Knebe, A., Kneib, J. -P., Kohley, R., Koopmans, L. V. E., Koskinen, H., Koulouridis, E., Kou, R., Kovács, A., Kovačić, I., Kowalczyk, A., Koyama, K., Kraljic, K., Krause, O., Kruk, S., Kubik, B., Kuchner, U., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lacasa, F., Lacey, C. G., La Franca, F., Lagarde, N., Lahav, O., Laigle, C., La Marca, A., La Marle, O., Lamine, B., Lam, M. C., Lançon, A., Landt, H., Langer, M., Lapi, A., Larcheveque, C., Larsen, S. S., Lattanzi, M., Laudisio, F., Laugier, D., Laureijs, R., Laurent, V., Lavaux, G., Lawrenson, A., Lazanu, A., Lazeyras, T., Boulc'h, Q. Le, Brun, A. M. C. Le, Brun, V. Le, Leclercq, F., Lee, S., Graet, J. Le, Legrand, L., Leirvik, K. N., Jeune, M. Le, Lembo, M., Mignant, D. Le, Lepinzan, M. D., Lepori, F., Reun, A. Le, Leroy, G., Lesci, G. F., Lesgourgues, J., Leuzzi, L., Levi, M. E., Liaudat, T. I., Libet, G., Liebing, P., Ligori, S., Lilje, P. B., Lin, C. -C., Linde, D., Linder, E., Lindholm, V., Linke, L., Li, S. -S., Liu, S. J., Lloro, I., Lobo, F. S. N., Lodieu, N., Lombardi, M., Lombriser, L., Lonare, P., Longo, G., López-Caniego, M., Lopez, X. Lopez, Alvarez, J. Lorenzo, Loureiro, A., Loveday, J., Lusso, E., Macias-Perez, J., Maciaszek, T., Maggio, G., Magliocchetti, M., Magnard, F., Magnier, E. A., Magro, A., Mahler, G., Mainetti, G., Maino, D., Maiorano, E., Malavasi, N., Mamon, G. A., Mancini, C., Mandelbaum, R., Manera, M., Manjón-García, A., Mannucci, F., Mansutti, O., Outeiro, M. Manteiga, Maoli, R., Maraston, C., Marcin, S., Marcos-Arenal, P., Margalef-Bentabol, B., Marggraf, O., Marinucci, D., Marinucci, M., Markovic, K., Marleau, F. R., Marpaud, J., Martignac, J., Martín-Fleitas, J., Martin-Moruno, P., Martin, E. L., Martinelli, M., Martinet, N., Martin, H., Martins, C. J. A. P., Marulli, F., Massari, D., Massey, R., Masters, D. C., Matarrese, S., Matsuoka, Y., Matthew, S., Maughan, B. J., Mauri, N., Maurin, L., Maurogordato, S., McCarthy, K., McConnachie, A. W., McCracken, H. J., McDonald, I., McEwen, J. D., McPartland, C. J. R., Medinaceli, E., Mehta, V., Mei, S., Melchior, M., Melin, J. -B., Ménard, B., Mendes, J., Mendez-Abreu, J., Meneghetti, M., Mercurio, A., Merlin, E., Metcalf, R. B., Meylan, G., Migliaccio, M., Mignoli, M., Miller, L., Miluzio, M., Milvang-Jensen, B., Mimoso, J. P., Miquel, R., Miyatake, H., Mobasher, B., Mohr, J. J., Monaco, P., Monguió, M., Montoro, A., Mora, A., Dizgah, A. Moradinezhad, Moresco, M., Moretti, C., Morgante, G., Morisset, N., Moriya, T. J., Morris, P. W., Mortlock, D. J., Moscardini, L., Mota, D. F., Mottet, S., Moustakas, L. A., Moutard, T., Müller, T., Munari, E., Murphree, G., Murray, C., Murray, N., Musi, P., Nadathur, S., Nagam, B. C., Nagao, T., Naidoo, K., Nakajima, R., Nally, C., Natoli, P., Navarro-Alsina, A., Girones, D. Navarro, Neissner, C., Nersesian, A., Nesseris, S., Nguyen-Kim, H. N., Nicastro, L., Nichol, R. C., Nielbock, M., Niemi, S. -M., Nieto, S., Nilsson, K., Noller, J., Norberg, P., Nouri-Zonoz, A., Ntelis, P., Nucita, A. A., Nugent, P., Nunes, N. J., Nutma, T., Ocampo, I., Odier, J., Oesch, P. A., Oguri, M., Oliveira, D. Magalhaes, Onoue, M., Oosterbroek, T., Oppizzi, F., Ordenovic, C., Osato, K., Pacaud, F., Pace, F., Padilla, C., Paech, K., Pagano, L., Page, M. J., Palazzi, E., Paltani, S., Pamuk, S., Pandolfi, S., Paoletti, D., Paolillo, M., Papaderos, P., Pardede, K., Parimbelli, G., Parmar, A., Partmann, C., Pasian, F., Passalacqua, F., Paterson, K., Patrizii, L., Pattison, C., Paulino-Afonso, A., Paviot, R., Peacock, J. A., Pearce, F. R., Pedersen, K., Peel, A., Peletier, R. F., Ibanez, M. Pellejero, Pello, R., Penny, M. T., Percival, W. J., Perez-Garrido, A., Perotto, L., Pettorino, V., Pezzotta, A., Pezzuto, S., Philippon, A., Pierre, M., Piersanti, O., Pietroni, M., Piga, L., Pilo, L., Pires, S., Pisani, A., Pizzella, A., Pizzuti, L., Plana, C., Polenta, G., Pollack, J. E., Poncet, M., Pöntinen, M., Pool, P., Popa, L. A., Popa, V., Popp, J., Porciani, C., Porth, L., Potter, D., Poulain, M., Pourtsidou, A., Pozzetti, L., Prandoni, I., Pratt, G. W., Prezelus, S., Prieto, E., Pugno, A., Quai, S., Quilley, L., Racca, G. D., Raccanelli, A., Rácz, G., Radinović, S., Radovich, M., Ragagnin, A., Ragnit, U., Raison, F., Ramos-Chernenko, N., Ranc, C., Rasera, Y., Raylet, N., Rebolo, R., Refregier, A., Reimberg, P., Reiprich, T. H., Renk, F., Renzi, A., Retre, J., Revaz, Y., Reylé, C., Reynolds, L., Rhodes, J., Ricci, F., Ricci, M., Riccio, G., Ricken, S. O., Rissanen, S., Risso, I., Rix, H. -W., Robin, A. C., Rocca-Volmerange, B., Rocci, P. -F., Rodenhuis, M., Rodighiero, G., Monroy, M. Rodriguez, Rollins, R. P., Romanello, M., Roman, J., Romelli, E., Romero-Gomez, M., Roncarelli, M., Rosati, P., Rosset, C., Rossetti, E., Roster, W., Rottgering, H. J. A., Rozas-Fernández, A., Ruane, K., Rubino-Martin, J. A., Rudolph, A., Ruppin, F., Rusholme, B., Sacquegna, S., Sáez-Casares, I., Saga, S., Saglia, R., Sahlén, M., Saifollahi, T., Sakr, Z., Salvalaggio, J., Salvaterra, R., Salvati, L., Salvato, M., Salvignol, J. -C., Sánchez, A. G., Sanchez, E., Sanders, D. B., Sapone, D., Saponara, M., Sarpa, E., Sarron, F., Sartori, S., Sartoris, B., Sassolas, B., Sauniere, L., Sauvage, M., Sawicki, M., Scaramella, R., Scarlata, C., Scharré, L., Schaye, J., Schewtschenko, J. A., Schindler, J. -T., Schinnerer, E., Schirmer, M., Schmidt, F., Schmidt, M., Schneider, A., Schneider, M., Schneider, P., Schöneberg, N., Schrabback, T., Schultheis, M., Schulz, S., Schuster, N., Schwartz, J., Sciotti, D., Scodeggio, M., Scognamiglio, D., Scott, D., Scottez, V., Secroun, A., Sefusatti, E., Seidel, G., Seiffert, M., Sellentin, E., Selwood, M., Semboloni, E., Sereno, M., Serjeant, S., Serrano, S., Setnikar, G., Shankar, F., Sharples, R. M., Short, A., Shulevski, A., Shuntov, M., Sias, M., Sikkema, G., Silvestri, A., Simon, P., Sirignano, C., Sirri, G., Skottfelt, J., Slezak, E., Sluse, D., Smith, G. P., Smith, L. C., Smith, R. E., Smit, S. J. A., Soldano, F., Solheim, B. G. B., Sorce, J. G., Sorrenti, F., Soubrie, E., Spinoglio, L., Mancini, A. Spurio, Stadel, J., Stagnaro, L., Stanco, L., Stanford, S. A., Starck, J. -L., Stassi, P., Steinwagner, J., Stern, D., Stone, C., Strada, P., Strafella, F., Stramaccioni, D., Surace, C., Sureau, F., Suyu, S. H., Swindells, I., Szafraniec, M., Szapudi, I., Taamoli, S., Talia, M., Tallada-Crespí, P., Tanidis, K., Tao, C., Tarrío, P., Tavagnacco, D., Taylor, A. N., Taylor, J. E., Taylor, P. L., Teixeira, E. M., Tenti, M., Idiago, P. Teodoro, Teplitz, H. I., Tereno, I., Tessore, N., Testa, V., Testera, G., Tewes, M., Teyssier, R., Theret, N., Thizy, C., Thomas, P. D., Toba, Y., Toft, S., Toledo-Moreo, R., Tolstoy, E., Tommasi, E., Torbaniuk, O., Torradeflot, F., Tortora, C., Tosi, S., Tosti, S., Trifoglio, M., Troja, A., Trombetti, T., Tronconi, A., Tsedrik, M., Tsyganov, A., Tucci, M., Tutusaus, I., Uhlemann, C., Ulivi, L., Urbano, M., Vacher, L., Vaillon, L., Valageas, P., Valdes, I., Valentijn, E. A., Valenziano, L., Valieri, C., Valiviita, J., Broeck, M. Van den, Vassallo, T., Vavrek, R., Vega-Ferrero, J., Venemans, B., Venhola, A., Ventura, S., Kleijn, G. Verdoes, Vergani, D., Verma, A., Vernizzi, F., Veropalumbo, A., Verza, G., Vescovi, C., Vibert, D., Viel, M., Vielzeuf, P., Viglione, C., Viitanen, A., Villaescusa-Navarro, F., Vinciguerra, S., Visticot, F., Voggel, K., von Wietersheim-Kramsta, M., Vriend, W. J., Wachter, S., Walmsley, M., Walth, G., Walton, D. M., Walton, N. A., Wander, M., Wang, L., Wang, Y., Weaver, J. R., Weller, J., Wetzstein, M., Whalen, D. J., Whittam, I. H., Widmer, A., Wiesmann, M., Wilde, J., Williams, O. R., Winther, H. -A., Wittje, A., Wong, J. H. W., Wright, A. H., Yankelevich, V., Yeung, H. W., Yoon, M., Youles, S., Yung, L. Y. A., Zacchei, A., Zalesky, L., Zamorani, G., Vitorelli, A. Zamorano, Marc, M. Zanoni, Zennaro, M., Zerbi, F. M., Zinchenko, I. A., Zoubian, J., Zucca, E., and Zumalacarregui, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'
Published: 2024

22. Euclid. II. The VIS Instrument

Author: Euclid Collaboration, Cropper, M., Al-Bahlawan, A., Amiaux, J., Awan, S., Azzollini, R., Benson, K., Berthe, M., Boucher, J., Bozzo, E., Brockley-Blatt, C., Candini, G. P., Cara, C., Chaudery, R. A., Cole, R. E., Danto, P., Denniston, J., Di Giorgio, A. M., Dryer, B., Endicott, J., Dubois, J. -P., Farina, M., Galli, E., Genolet, L., Gow, J. P. D., Guttridge, P., Hailey, M., Hall, D., Harper, C., Holland, A. D., Horeau, B., Hu, D., King, R., James, R. E., Larcheveque, C., Khalil, A., Lawrenson, A., Liebing, P., Martignac, J., McCracken, H. J., Murray, N., Nakajima, R., Niemi, S. -M., Pendem, A., Paltani, S., Philippon, A., Pool, P., Plana, C., Pottinger, S., Racca, G. D., Rousseau, A., Ruane, K., Salatti, M., Salvignol, J. -C., Sciortino, A., Short, Alexander, Liu, S. J., Skottfelt, J., Swindells, I., Smit, S. J. A., Szafraniec, M., Thomas, P. D., Thomas, W., Tommasi, E., Winter, B., Tosti, S., Visticot, F., Walton, D. M., Willis, G., Mora, A., Kohley, R., Massey, R., Nightingale, J. W., Kitching, T., Hoekstra, H., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Aussel, H., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Bender, R., Bodendorf, C., Boenke, T., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, R., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cuby, J. -G., Cuillandre, J. -C., Da Silva, A., Degaudenzi, H., Dinis, J., Dolding, C., Douspis, M., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Fabricius, M., Farrens, S., Ferriol, S., Fosalba, P., Fotopoulou, S., Frailis, M., Franceschi, E., Franzetti, P., Frugier, P. -A., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Herent, O., Hoar, J., Holliman, M. S., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kilbinger, M., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Alvarez, J. Lorenzo, Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Martinet, N., Marulli, F., Masters, D. C., Maurogordato, S., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Miller, L., Mohr, J. J., Moresco, M., Moscardini, L., Nichol, R. C., Nutma, T., Padilla, C., Paech, K., Pasian, F., Peacock, J. A., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Refregier, A., Renzi, A., Riccio, G., Rix, Hans-Walter, Romelli, E., Roncarelli, M., Rosset, C., Rossetti, E., Rottgering, H. J. A., Saglia, R., Sapone, D., Sauvage, M., Scaramella, R., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wachter, S., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Baccigalupi, C., Bernardeau, F., Biviano, A., Bolzonella, M., Boucaud, A., Burigana, C., Calabrese, M., Casenove, P., Colodro-Conde, C., Crocce, M., De Lucia, G., Di Ferdinando, D., Vigo, J. A. Escartin, Fabbian, G., Farinelli, R., Finelli, F., George, K., Gracia-Carpio, J., Ilić, S., Israel, H., Mainetti, G., Marcin, S., Martinelli, M., Mauri, N., Neissner, C., Nguyen-Kim, H. N., Pezzotta, A., Pöntinen, M., Porciani, C., Sakr, Z., Scottez, V., Sefusatti, E., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Aubourg, E., Ballardini, M., Bertacca, D., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Calabro, A., Calderone, G., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Chary, R., Contarini, S., Cooray, A. R., Cordes, O., Costanzi, M., Cucciati, O., Davini, S., De Caro, B., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Gregorio, A., Hall, A., Hartley, W. G., Hildebrandt, H., Hjorth, J., Huertas-Company, M., Ilbert, O., Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Lacasa, F., Graet, J. Le, Legrand, L., Libet, G., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., McPartland, C. J. R., Metcalf, R. B., Migliaccio, M., Miluzio, M., Monaco, P., Moretti, C., Morgante, G., Nadathur, S., Walton, Nicholas A., Odier, J., Oguri, M., Patrizii, L., Popa, V., Potter, D., Pourtsidou, A., Reimberg, P., Risso, I., Rocci, P. -F., Rollins, R. P., Rusholme, B., Sahlén, M., Sánchez, A. G., Scarlata, C., Schaye, J., Schewtschenko, J. A., Schneider, A., Schultheis, M., Sereno, M., Shankar, F., Sikkema, G., Silvestri, A., Simon, P., Mancini, A. Spurio, Stadel, J., Stanford, S. A., Steinwagner, J., Tanidis, K., Tao, C., Tessore, N., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Vernizzi, F., Verza, G., Vielzeuf, P., Weaver, J. R., Zalesky, L., Zinchenko, I. A., Archidiacono, M., Atrio-Barandela, F., Bouvard, T., Caro, F., Dimauro, P., Duc, P. -A., Fang, Y., Ferguson, A. M. N., Gasparetto, T., Gutierrez, C. M., Kova{č}ić, I., Kruk, S., Brun, A. M. C. Le, Liaudat, T. I., Montoro, A., Murray, C., Pagano, L., Paoletti, D., Sarpa, E., Viitanen, A., Lesgourgues, J., and Martín-Fleitas, J.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: This paper presents the specification, design, and development of the Visible Camera (VIS) on the ESA Euclid mission. VIS is a large optical-band imager with a field of view of 0.54 deg^2 sampled at 0.1" with an array of 609 Megapixels and spatial resolution of 0.18". It will be used to survey approximately 14,000 deg^2 of extragalactic sky to measure the distortion of galaxies in the redshift range z=0.1-1.5 resulting from weak gravitational lensing, one of the two principal cosmology probes of Euclid. With photometric redshifts, the distribution of dark matter can be mapped in three dimensions, and, from how this has changed with look-back time, the nature of dark energy and theories of gravity can be constrained. The entire VIS focal plane will be transmitted to provide the largest images of the Universe from space to date, reaching m_AB>24.5 with S/N >10 in a single broad I_E~(r+i+z) band over a six year survey. The particularly challenging aspects of the instrument are the control and calibration of observational biases, which lead to stringent performance requirements and calibration regimes. With its combination of spatial resolution, calibration knowledge, depth, and area covering most of the extra-Galactic sky, VIS will also provide a legacy data set for many other fields. This paper discusses the rationale behind the VIS concept and describes the instrument design and development before reporting the pre-launch performance derived from ground calibrations and brief results from the in-orbit commissioning. VIS should reach fainter than m_AB=25 with S/N>10 for galaxies of full-width half-maximum of 0.3" in a 1.3" diameter aperture over the Wide Survey, and m_AB>26.4 for a Deep Survey that will cover more than 50 deg^2. The paper also describes how VIS works with the other Euclid components of survey, telescope, and science data processing to extract the cosmological information., Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations
Published: 2024

23. Euclid preparation. Sensitivity to neutrino parameters

Author: Euclid Collaboration, Archidiacono, M., Lesgourgues, J., Casas, S., Pamuk, S., Schöneberg, N., Sakr, Z., Parimbelli, G., Schneider, A., Peters, F. Hervas, Pace, F., Sabarish, V. M., Costanzi, M., Camera, S., Carbone, C., Clesse, S., Frusciante, N., Fumagalli, A., Monaco, P., Scott, D., Viel, M., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Cardone, V. F., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sapone, D., Sartoris, B., Scaramella, R., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Colodro-Conde, C., Crocce, M., Fabbian, G., Graciá-Carpio, J., Mainetti, G., Martinelli, M., Mauri, N., Neissner, C., Scottez, V., Tenti, M., Wiesmann, M., Akrami, Y., Anselmi, S., Baccigalupi, C., Ballardini, M., Bernardeau, F., Bertacca, D., Borgani, S., Borsato, E., Bruton, S., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Contarini, S., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Di Domizio, S., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferreira, P. G., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Gregorio, A., Hall, A., Hildebrandt, H., Ilić, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Morgante, G., Nadathur, S., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Sánchez, A. G., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., and Vielzeuf, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Euclid mission of the European Space Agency will deliver weak gravitational lensing and galaxy clustering surveys that can be used to constrain the standard cosmological model and extensions thereof. We present forecasts from the combination of these surveys on the sensitivity to cosmological parameters including the summed neutrino mass $M_\nu$ and the effective number of relativistic species $N_{\rm eff}$ in the standard $\Lambda$CDM scenario and in a scenario with dynamical dark energy ($w_0 w_a$CDM). We compare the accuracy of different algorithms predicting the nonlinear matter power spectrum for such models. We then validate several pipelines for Fisher matrix and MCMC forecasts, using different theory codes, algorithms for numerical derivatives, and assumptions concerning the non-linear cut-off scale. The Euclid primary probes alone will reach a sensitivity of $\sigma(M_\nu)=$56meV in the $\Lambda$CDM+$M_\nu$ model, whereas the combination with CMB data from Planck is expected to achieve $\sigma(M_\nu)=$23meV and raise the evidence for a non-zero neutrino mass to at least the $2.6\sigma$ level. This can be pushed to a $4\sigma$ detection if future CMB data from LiteBIRD and CMB Stage-IV are included. In combination with Planck, Euclid will also deliver tight constraints on $\Delta N_{\rm eff}< 0.144$ (95%CL) in the $\Lambda$CDM+$M_\nu$+$N_{\rm eff}$ model, or $\Delta N_{\rm eff}< 0.063$ when future CMB data are included. When floating $(w_0, w_a)$, we find that the sensitivity to $N_{\rm eff}$ remains stable, while that to $M_\nu$ degrades at most by a factor 2. This work illustrates the complementarity between the Euclid spectroscopic and imaging/photometric surveys and between Euclid and CMB constraints. Euclid will have a great potential for measuring the neutrino mass and excluding well-motivated scenarios with additional relativistic particles., Comment: 48 pages, 33 figures
Published: 2024

24. Euclid preparation. LensMC, weak lensing cosmic shear measurement with forward modelling and Markov Chain Monte Carlo sampling

Author: Euclid Collaboration, Congedo, G., Miller, L., Taylor, A. N., Cross, N., Duncan, C. A. J., Kitching, T., Martinet, N., Matthew, S., Schrabback, T., Tewes, M., Welikala, N., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holliman, M. S., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Morin, B., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Tavagnacco, D., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Guinet, D., Hall, A., Hildebrandt, H., Ilić, S., Muñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Macias-Perez, J., Maggio, G., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Peel, A., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schewtschenko, J. A., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., and Vergani, D.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Physics - Data Analysis, Statistics and Probability, Statistics - Computation
Abstract: LensMC is a weak lensing shear measurement method developed for Euclid and Stage-IV surveys. It is based on forward modelling to deal with convolution by a point spread function with comparable size to many galaxies; sampling the posterior distribution of galaxy parameters via Markov Chain Monte Carlo; and marginalisation over nuisance parameters for each of the 1.5 billion galaxies observed by Euclid. The scientific performance is quantified through high-fidelity images based on the Euclid Flagship simulations and emulation of the Euclid VIS images; realistic clustering with a mean surface number density of 250 arcmin$^{-2}$ ($I_{\rm E}<29.5$) for galaxies, and 6 arcmin$^{-2}$ ($I_{\rm E}<26$) for stars; and a diffraction-limited chromatic point spread function with a full width at half maximum of $0.^{\!\prime\prime}2$ and spatial variation across the field of view. Objects are measured with a density of 90 arcmin$^{-2}$ ($I_{\rm E}<26.5$) in 4500 deg$^2$. The total shear bias is broken down into measurement (our main focus here) and selection effects (which will be addressed elsewhere). We find: measurement multiplicative and additive biases of $m_1=(-3.6\pm0.2)\times10^{-3}$, $m_2=(-4.3\pm0.2)\times10^{-3}$, $c_1=(-1.78\pm0.03)\times10^{-4}$, $c_2=(0.09\pm0.03)\times10^{-4}$; a large detection bias with a multiplicative component of $1.2\times10^{-2}$ and an additive component of $-3\times10^{-4}$; and a measurement PSF leakage of $\alpha_1=(-9\pm3)\times10^{-4}$ and $\alpha_2=(2\pm3)\times10^{-4}$. When model bias is suppressed, the obtained measurement biases are close to Euclid requirement and largely dominated by undetected faint galaxies ($-5\times10^{-3}$). Although significant, model bias will be straightforward to calibrate given the weak sensitivity. LensMC is publicly available at https://gitlab.com/gcongedo/LensMC, Comment: 29 pages, 18 figures, 2 tables
Published: 2024

25. Euclid preparation. Improving cosmological constraints using a new multi-tracer method with the spectroscopic and photometric samples

Author: Euclid Collaboration, Dournac, F., Blanchard, A., Ilić, S., Lamine, B., Tutusaus, I., Amara, A., Andreon, S., Auricchio, N., Aussel, H., Baldi, M., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brau-Nogue, S., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Gillard, W., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Schneider, P., Secroun, A., Seidel, G., Seiffert, M., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., De Lucia, G., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., Gracia-Carpio, J., Mainetti, G., Martinelli, M., Mauri, N., Neissner, C., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Balaguera-Antolinez, A., Ballardini, M., Blot, L., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., Coupon, J., Davini, S., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Munoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Libet, G., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Moretti, C., Morgante, G., Nadathur, S., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Sánchez, A. G., Schewtschenko, J. A., Schneider, A., Sefusatti, E., Sereno, M., Steinwagner, J., Tessore, N., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Vergani, D., and Verza, G.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Future data provided by the Euclid mission will allow us to better understand the cosmic history of the Universe. A metric of its performance is the figure-of-merit (FoM) of dark energy, usually estimated with Fisher forecasts. The expected FoM has previously been estimated taking into account the two main probes of Euclid, namely the three-dimensional clustering of the spectroscopic galaxy sample, and the so-called 3x2pt signal from the photometric sample (i.e., the weak lensing signal, the galaxy clustering, and their cross-correlation). So far, these two probes have been treated as independent. In this paper, we introduce a new observable given by the ratio of the (angular) two-point correlation function of galaxies from the two surveys. For identical (normalised) selection functions, this observable is unaffected by sampling noise, and its variance is solely controlled by Poisson noise. We present forecasts for Euclid where this multi-tracer method is applied and is particularly relevant because the two surveys will cover the same area of the sky. This method allows for the exploitation of the combination of the spectroscopic and photometric samples. When the correlation between this new observable and the other probes is not taken into account, a significant gain is obtained in the FoM, as well as in the constraints on other cosmological parameters. The benefit is more pronounced for a commonly investigated modified gravity model, namely the $\gamma$ parametrisation of the growth factor. However, the correlation between the different probes is found to be significant and hence the actual gain is uncertain. We present various strategies for circumventing this issue and still extract useful information from the new observable., Comment: 16 pages, 7 figures, submitted to A&A
Published: 2024
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26. Euclid preparation. XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning

Author: Euclid Collaboration, Aussel, B., Kruk, S., Walmsley, M., Huertas-Company, M., Castellano, M., Conselice, C. J., Veneri, M. Delli, Sánchez, H. Domínguez, Duc, P. -A., Kuchner, U., La Marca, A., Margalef-Bentabol, B., Marleau, F. R., Stevens, G., Toba, Y., Tortora, C., Wang, L., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mainetti, G., Marcin, S., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Borgani, S., Borlaff, A. S., Bretonnière, H., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Coupon, J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., George, K., Giacomini, F., Gozaliasl, G., Gregorio, A., Guinet, D., Hall, A., Hildebrandt, H., Munoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Walton, Nicholas A., Peel, A., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Stanford, S. A., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., and Zinchenko, I. A.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in Euclid using Zoobot a convolutional neural network pretrained with 450000 galaxies from the Galaxy Zoo project. We adapted Zoobot for emulated Euclid images, generated based on Hubble Space Telescope COSMOS images, and with labels provided by volunteers in the Galaxy Zoo: Hubble project. We demonstrate that the trained Zoobot model successfully measures detailed morphology for emulated Euclid images. It effectively predicts whether a galaxy has features and identifies and characterises various features such as spiral arms, clumps, bars, disks, and central bulges. When compared to volunteer classifications Zoobot achieves mean vote fraction deviations of less than 12% and an accuracy above 91% for the confident volunteer classifications across most morphology types. However, the performance varies depending on the specific morphological class. For the global classes such as disk or smooth galaxies, the mean deviations are less than 10%, with only 1000 training galaxies necessary to reach this performance. For more detailed structures and complex tasks like detecting and counting spiral arms or clumps, the deviations are slightly higher, around 12% with 60000 galaxies used for training. In order to enhance the performance on complex morphologies, we anticipate that a larger pool of labelled galaxies is needed, which could be obtained using crowdsourcing. Finally, our findings imply that the model can be effectively adapted to new morphological labels. We demonstrate this adaptability by applying Zoobot to peculiar galaxies. In summary, our trained Zoobot CNN can readily predict morphological catalogues for Euclid images., Comment: 27 pages, 26 figures, 5 tables, published in A&A
Published: 2024
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27. Euclid preparation. Optical emission-line predictions of intermediate-z galaxy populations in GAEA for the Euclid Deep and Wide Surveys

Author: Euclid Collaboration, Scharré, L., Hirschmann, M., De Lucia, G., Charlot, S., Fontanot, F., Spinelli, M., Xie, L., Feltre, A., Allevato, V., Plat, A., Bremer, M. N., Fotopoulou, S., Gabarra, L., Granett, B. R., Moresco, M., Scarlata, C., Pozzetti, L., Spinoglio, L., Talia, M., Zamorani, G., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kitching, T., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mainetti, G., Martinelli, M., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Baccigalupi, C., Ballardini, M., Bethermin, M., Blanchard, A., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Calabro, A., Cañas-Herrera, G., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Contarini, S., Contini, T., Cooray, A. R., Coupon, J., Cucciati, O., Desprez, G., Di Domizio, S., Dole, H., ánchez, A. Díaz-S, Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Ganga, K., García-Bellido, J., Gaztanaga, E., George, K., Giacomini, F., Gozaliasl, G., Gregorio, A., Hall, A., Hildebrandt, H., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Walton, Nicholas A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Sánchez, A. G., Schneider, A., Schultheis, M., Sereno, M., Simon, P., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Vergani, D., Verza, G., and Zinchenko, I. A.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: In anticipation of the Euclid Wide and Deep Surveys, we present optical emission-line predictions at intermediate redshifts from 0.4 to 2.5. Our approach combines a mock light cone from the GAEA semi-analytic model to self-consistently model nebular emission from HII regions, narrow-line regions of active galactic nuclei (AGN), and evolved stellar populations. Our analysis focuses on seven optical emission lines: H$\alpha$, H$\beta$, [SII]$\lambda\lambda 6717, 6731$, [NII]$\lambda 6584$, [OI]$\lambda 6300$, [OIII]$\lambda 5007$, and [OII]$\lambda\lambda 3727, 3729$. We find that Euclid will predominantly observe massive, star-forming, and metal-rich line-emitters. Interstellar dust, modelled using a Calzetti law with mass-dependent scaling, may decrease observable percentages by a further 20-30% with respect to our underlying emission-line populations from GAEA. We predict Euclid to observe around 30-70% of H$\alpha$-, [NII]-, [SII]-, and [OIII]-emitting galaxies at redshift below 1 and under 10% at higher redshift. Observability of H$\beta$-, [OII]-, and [OI]- emission is limited to below 5%. For the Euclid-observable sample, we find that BPT diagrams can effectively distinguish between different galaxy types up to around redshift 1.8, attributed to the bias toward metal-rich systems. Moreover, we show that the relationships of H$\alpha$ and [OIII]+H$\beta$ to the star-formation rate, and the [OIII]-AGN luminosity relation, exhibit minimal changes with increasing redshift. Based on line ratios [NII]/H$\alpha$, [NII]/[OII], and [NII]/[SII], we further propose novel z-invariant tracers for the black hole accretion rate-to-star formation rate ratio. Lastly, we find that commonly used metallicity estimators display gradual shifts in normalisations with increasing redshift, while maintaining the overall shape of local calibrations. This is in tentative agreement with recent JWST data., Comment: 32 pages, 15 figures, submitted to A&A
Published: 2024
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28. Euclid preparation XLVI. The Near-IR Background Dipole Experiment with Euclid

Author: Euclid Collaboration, Kashlinsky, A., Arendt, R. G., Ashby, M. L. N., Atrio-Barandela, F., Scaramella, R., Strauss, M. A., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Seiffert, M., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Fabbian, G., Farinelli, R., Graciá-Carpio, J., Mainetti, G., Martinelli, M., Mauri, N., Neissner, C., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Blanchard, A., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Contarini, S., Coupon, J., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Ferrero, I., Finelli, F., Gabarra, L., García-Bellido, J., Gautard, V., Gaztanaga, E., George, K., Giacomini, F., Gozaliasl, G., Gregorio, A., Hall, A., Hildebrandt, H., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Walton, Nicholas A., Patrizii, L., Popa, V., Potter, D., Pöntinen, M., Rocci, P. -F., Sahlén, M., Schneider, A., Sefusatti, E., Sereno, M., Steinwagner, J., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Vergani, D., Verza, G., and Hasinger, G.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract: Verifying the fully kinematic nature of the cosmic microwave background (CMB) dipole is of fundamental importance in cosmology. In the standard cosmological model with the Friedman-Lemaitre-Robertson-Walker (FLRW) metric from the inflationary expansion the CMB dipole should be entirely kinematic. Any non-kinematic CMB dipole component would thus reflect the preinflationary structure of spacetime probing the extent of the FLRW applicability. Cosmic backgrounds from galaxies after the matter-radiation decoupling, should have kinematic dipole component identical in velocity with the CMB kinematic dipole. Comparing the two can lead to isolating the CMB non-kinematic dipole. It was recently proposed that such measurement can be done using the near-IR cosmic infrared background (CIB) measured with the currently operating Euclid telescope, and later with Roman. The proposed method reconstructs the resolved CIB, the Integrated Galaxy Light (IGL), from Euclid's Wide Survey and probes its dipole, with a kinematic component amplified over that of the CMB by the Compton-Getting effect. The amplification coupled with the extensive galaxy samples forming the IGL would determine the CIB dipole with an overwhelming signal/noise, isolating its direction to sub-degree accuracy. We develop details of the method for Euclid's Wide Survey in 4 bands spanning 0.6 to 2 mic. We isolate the systematic and other uncertainties and present methodologies to minimize them, after confining the sample to the magnitude range with negligible IGL/CIB dipole from galaxy clustering. These include the required star-galaxy separation, accounting for the extinction correction dipole using the method newly developed here achieving total separation, accounting for the Earth's orbital motion and other systematic effects. (Abridged), Comment: Euclid Key Project paper, A&A, in press
Published: 2024

29. Euclid preparation: XLVIII. The pre-launch Science Ground Segment simulation framework

Author: Euclid Collaboration, Serrano, S., Hudelot, P., Seidel, G., Pollack, J. E., Jullo, E., Torradeflot, F., Benielli, D., Fahed, R., Auphan, T., Carretero, J., Aussel, H., Casenove, P., Castander, F. J., Davies, J. E., Fourmanoit, N., Huot, S., Kara, A., Keihänen, E., Kermiche, S., Okumura, K., Zoubian, J., Ealet, A., Boucaud, A., Bretonnière, H., Casas, R., Clément, B., Duncan, C. A. J., George, K., Kiiveri, K., Kurki-Suonio, H., Kümmel, M., Laugier, D., Mainetti, G., Mohr, J. J., Montoro, A., Neissner, C., Rosset, C., Schirmer, M., Tallada-Crespí, P., Tonello, N., Venhola, A., Verderi, A., Zacchei, A., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Azzollini, R., Baccigalupi, C., Baldi, M., Bardelli, S., Basset, A., Battaglia, P., Bernardeau, F., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Cledassou, R., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Crocce, M., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Kiessling, A., Kitching, T., Kohley, R., Kunz, M., Boulc'h, Q. Le, Liebing, P., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Morris, P., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. -M., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Rusholme, B., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Sauvage, M., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. -L., Steinwagner, J., Taylor, A. N, Teplitz, H., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bozzo, E., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mauri, N., Scottez, V., Tenti, M., Akrami, Y., Allevato, V., Ballardini, M., Blanchard, A., Borgani, S., Borlaff, A. S., Bruton, S., Burigana, C., Cappi, A., Carvalho, C. S., Castro, T., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., Desai, S., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Gregorio, A., Hildebrandt, H., Huertas-Company, M., Ilbert, O., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Schneider, A., Sereno, M., Shulevski, A., Simon, P., Mancini, A. Spurio, Stadel, J., Tewes, M., Teyssier, R., Toft, S., Tucci, M., Valiviita, J., Viel, M., and Zinchenko, I. A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The European Space Agency's Euclid mission is one of the upcoming generation of large-scale cosmology surveys, which will map the large-scale structure in the Universe with unprecedented precision. The development and validation of the SGS pipeline requires state-of-the-art simulations with a high level of complexity and accuracy that include subtle instrumental features not accounted for previously as well as faster algorithms for the large-scale production of the expected Euclid data products. In this paper, we present the Euclid SGS simulation framework as applied in a large-scale end-to-end simulation exercise named Science Challenge 8. Our simulation pipeline enables the swift production of detailed image simulations for the construction and validation of the Euclid mission during its qualification phase and will serve as a reference throughout operations. Our end-to-end simulation framework starts with the production of a large cosmological N-body & mock galaxy catalogue simulation. We perform a selection of galaxies down to I_E=26 and 28 mag, respectively, for a Euclid Wide Survey spanning 165 deg^2 and a 1 deg^2 Euclid Deep Survey. We build realistic stellar density catalogues containing Milky Way-like stars down to H<26. Using the latest instrumental models for both the Euclid instruments and spacecraft as well as Euclid-like observing sequences, we emulate with high fidelity Euclid satellite imaging throughout the mission's lifetime. We present the SC8 data set consisting of overlapping visible and near-infrared Euclid Wide Survey and Euclid Deep Survey imaging and low-resolution spectroscopy along with ground-based. This extensive data set enables end-to-end testing of the entire ground segment data reduction and science analysis pipeline as well as the Euclid mission infrastructure, paving the way to future scientific and technical developments and enhancements., Comment: 39 pages, 25 figures, A&A submitted
Published: 2024

30. Euclid Preparation. XXXVII. Galaxy colour selections with Euclid and ground photometry for cluster weak-lensing analyses

Author: Euclid Collaboration, Lesci, G. F., Sereno, M., Radovich, M., Castignani, G., Bisigello, L., Marulli, F., Moscardini, L., Baumont, L., Covone, G., Farrens, S., Giocoli, C., Ingoglia, L., La Hera, S. Miranda, Vannier, M., Biviano, A., Maurogordato, S., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Ferriol, S., Fosalba, P., Fotopoulou, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Grazian, A., Grupp, F., Haugan, S. V. H., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Massey, R., Medinaceli, E., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Munari, E., Nakajima, R., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Bolzonella, M., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Marcin, S., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Baccigalupi, C., Ballardini, M., Borgani, S., Borlaff, A. S., Bruton, S., Burigana, C., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castro, T., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Cucciati, O., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Giacomini, F., Gozaliasl, G., Gwyn, S., Hildebrandt, H., Huertas-Company, M., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mainetti, G., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Pezzotta, A., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Schultheis, M., Sefusatti, E., Simon, P., Mancini, A. Spurio, Stanford, S. A., Steinwagner, J., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., and Vergani, D.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: We derived galaxy colour selections from Euclid and ground-based photometry, aiming to accurately define background galaxy samples in cluster weak-lensing analyses. Given any set of photometric bands, we developed a method for the calibration of optimal galaxy colour selections that maximises the selection completeness, given a threshold on purity. We calibrated galaxy selections using simulated ground-based $griz$ and Euclid $Y_{\rm E}J_{\rm E}H_{\rm E}$ photometry. Both selections produce a purity higher than 97%. The $griz$ selection completeness ranges from 30% to 84% in the lens redshift range $z_{\rm l}\in[0.2,0.8]$. With the full $grizY_{\rm E}J_{\rm E}H_{\rm E}$ selection, the completeness improves by up to $25$ percentage points, and the $z_{\rm l}$ range extends up to $z_{\rm l}=1.5$. The calibrated colour selections are stable to changes in the sample limiting magnitudes and redshift, and the selection based on $griz$ bands provides excellent results on real external datasets. The $griz$ selection is also purer at high redshift and more complete at low redshift compared to colour selections found in the literature. We find excellent agreement in terms of purity and completeness between the analysis of an independent, simulated Euclid galaxy catalogue and our calibration sample, except for galaxies at high redshifts, for which we obtain up to 50 percent points higher completeness. The combination of colour and photo-$z$ selections applied to simulated Euclid data yields up to 95% completeness, while the purity decreases down to 92% at high $z_{\rm l}$. We show that the calibrated colour selections provide robust results even when observations from a single band are missing from the ground-based data. Finally, we show that colour selections do not disrupt the shear calibration for stage III surveys., Comment: 20 pages, 13 figures. Published by A&A
Published: 2023

31. Euclid preparation. Modelling spectroscopic clustering on mildly nonlinear scales in beyond-$\Lambda$CDM models

Author: Euclid Collaboration, Bose, B., Carrilho, P., Marinucci, M., Moretti, C., Pietroni, M., Carella, E., Piga, L., Wright, B. S., Vernizzi, F., Carbone, C., Casas, S., D'Amico, G., Frusciante, N., Koyama, K., Pace, F., Pourtsidou, A., Baldi, M., de la Bella, L. F., Fiorini, B., Giocoli, C., Lombriser, L., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Cardone, V. F., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Costille, A., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillis, B., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Seiffert, M., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Mauri, N., Neissner, C., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Ballardini, M., Bernardeau, F., Borgani, S., Bruton, S., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferreira, P. G., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Giacomini, F., Gozaliasl, G., Guinet, D., Hall, A., Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sefusatti, E., Sereno, M., Silvestri, A., Mancini, A. Spurio, Steinwagner, J., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., and Vergani, D.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We investigate the approximations needed to efficiently predict the large-scale clustering of matter and dark matter halos in beyond-$\Lambda$CDM scenarios. We examine the normal branch of the Dvali-Gabadadze-Porrati model, the Hu-Sawicki $f(R)$ model, a slowly evolving dark energy, an interacting dark energy model and massive neutrinos. For each, we test approximations for the perturbative kernel calculations, including the omission of screening terms and the use of perturbative kernels based on the Einstein-de Sitter universe; we explore different infrared-resummation schemes, tracer bias models and a linear treatment of massive neutrinos; we employ two models for redshift space distortions, the Taruya-Nishimishi-Saito prescription and the Effective Field Theory of Large-Scale Structure. This work further provides a preliminary validation of the codes being considered by Euclid for the spectroscopic clustering probe in beyond-$\Lambda$CDM scenarios. We calculate and compare the $\chi^2$ statistic to assess the different modelling choices. This is done by fitting the spectroscopic clustering predictions to measurements from numerical simulations and perturbation theory-based mock data. We compare the behaviour of this statistic in the beyond-$\Lambda$CDM cases, as a function of the maximum scale included in the fit, to the baseline $\Lambda$CDM case. We find that the Einstein-de Sitter approximation without screening is surprisingly accurate for all cases when comparing to the halo clustering monopole and quadrupole obtained from simulations. Our results suggest that the inclusion of multiple redshift bins, higher-order multipoles, higher-order clustering statistics (such as the bispectrum) and photometric probes such as weak lensing, will be essential to extract information on massive neutrinos, modified gravity and dark energy., Comment: 29 pages, 10 figures, 4 tables, 3 appendices. Journal accepted version
Published: 2023
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32. Euclid preparation. Spectroscopy of active galactic nuclei with NISP

Author: Euclid Collaboration, Lusso, E., Fotopoulou, S., Selwood, M., Allevato, V., Calderone, G., Mancini, C., Mignoli, M., Scodeggio, M., Bisigello, L., Feltre, A., Ricci, F., La Franca, F., Vergani, D., Gabarra, L., Brun, V. Le, Maiorano, E., Palazzi, E., Moresco, M., Zamorani, G., Cresci, G., Jahnke, K., Humphrey, A., Landt, H., Mannucci, F., Marconi, A., Pozzetti, L., Salucci, P., Salvato, M., Shankar, F., Spinoglio, L., Stern, D., Serjeant, S., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auphan, T., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fourmanoit, N., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Kümmel, M., Keihänen, E., Kermiche, S., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Mellier, Y., Merlin, E., Meylan, G., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Vibert, D., Wang, Y., Weller, J., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Mainetti, G., Mauri, N., Neissner, C., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Baccigalupi, C., Ballardini, M., Bethermin, M., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Ganga, K., García-Bellido, J., Giacomini, F., Gozaliasl, G., Guinet, D., Hall, A., Hildebrandt, H., Muñoz, A. Jiminez, Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sefusatti, E., Sereno, M., Shulevski, A., Simon, P., Mancini, A. Spurio, Stadel, J., Stanford, S. A., Steinwagner, J., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., and Zinchenko, I. A.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: The statistical distribution and evolution of key properties (e.g. accretion rate, mass, or spin) of active galactic nuclei (AGN), remain an open debate in astrophysics. The ESA Euclid space mission, launched on July 1st 2023, promises a breakthrough in this field. We create detailed mock catalogues of AGN spectra, from the rest-frame near-infrared down to the ultraviolet, including emission lines, to simulate what Euclid will observe for both obscured (type 2) and unobscured (type 1) AGN. We concentrate on the red grisms of the NISP instrument, which will be used for the wide-field survey, opening a new window for spectroscopic AGN studies in the near-infrared. We quantify the efficiency in the redshift determination as well as in retrieving the emission line flux of the H$\alpha$+[NII] complex as Euclid is mainly focused on this emission line as it is expected to be the brightest one in the probed redshift range. Spectroscopic redshifts are measured for 83% of the simulated AGN in the interval where the H$\alpha$+[NII] is visible (0.892x10^{-16}$ erg s$^{-1}$ cm$^{-2}$, encompassing the peak of AGN activity at $z\simeq 1-1.5$) within the spectral coverage of the red grism. Outside this redshift range, the measurement efficiency decreases significantly. Overall, a spectroscopic redshift is correctly determined for ~90% of type 2 AGN down to an emission line flux of $3x10^{-16}$ erg s$^{-1}$ cm$^{-2}$, and for type 1 AGN down to $8.5x10^{-16}$ erg s$^{-1}$ cm$^{-2}$. Recovered black hole mass values show a small offset with respect to the input values ~10%, but the agreement is good overall. With such a high spectroscopic coverage at z<2, we will be able to measure AGN demography, scaling relations, and clustering from the epoch of the peak of AGN activity down to the present-day Universe for hundreds of thousand AGN with homogeneous spectroscopic information., Comment: 29 pages, 23 figures. Submitted to A&A, revised version
Published: 2023

33. Euclid Preparation. TBD. Impact of magnification on spectroscopic galaxy clustering

Author: Euclid Collaboration, Jelic-Cizmek, G., Sorrenti, F., Lepori, F., Bonvin, C., Camera, S., Castander, F. J., Durrer, R., Fosalba, P., Kunz, M., Lombriser, L., Tutusaus, I., Viglione, C., Sakr, Z., Aghanim, N., Amara, A., Andreon, S., Baldi, M., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Cropper, M., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Meneghetti, M., Merlin, E., Meylan, G., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Surace, C., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Liebing, P., Mauri, N., Neissner, C., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Bruton, S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., {n}as-Herrera, G. Ca\, Chambers, K. C., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferreira, P. G., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Giacomini, F., Gozaliasl, G., Guinet, D., Hildebrandt, H., Ilić, S., {n}oz, A. Jimenez Mu\, Joudaki, S., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Magliocchetti, M., Mainetti, G., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Schultheis, M., Sefusatti, E., Sereno, M., Silvestri, A., Simon, P., Mancini, A. Spurio, Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Vergani, D., and Tanidis, K.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: In this paper we investigate the impact of lensing magnification on the analysis of Euclid's spectroscopic survey, using the multipoles of the 2-point correlation function for galaxy clustering. We determine the impact of lensing magnification on cosmological constraints, and the expected shift in the best-fit parameters if magnification is ignored. We consider two cosmological analyses: i) a full-shape analysis based on the $\Lambda$CDM model and its extension $w_0w_a$CDM and ii) a model-independent analysis that measures the growth rate of structure in each redshift bin. We adopt two complementary approaches in our forecast: the Fisher matrix formalism and the Markov chain Monte Carlo method. The fiducial values of the local count slope (or magnification bias), which regulates the amplitude of the lensing magnification, have been estimated from the Euclid Flagship simulations. We use linear perturbation theory and model the 2-point correlation function with the public code coffe. For a $\Lambda$CDM model, we find that the estimation of cosmological parameters is biased at the level of 0.4-0.7 standard deviations, while for a $w_0w_a$CDM dynamical dark energy model, lensing magnification has a somewhat smaller impact, with shifts below 0.5 standard deviations. In a model-independent analysis aiming to measure the growth rate of structure, we find that the estimation of the growth rate is biased by up to $1.2$ standard deviations in the highest redshift bin. As a result, lensing magnification cannot be neglected in the spectroscopic survey, especially if we want to determine the growth factor, one of the most promising ways to test general relativity with Euclid. We also find that, by including lensing magnification with a simple template, this shift can be almost entirely eliminated with minimal computational overhead., Comment: 23 pages, 14 figures
Published: 2023

34. Euclid preparation. TBD. Forecast impact of super-sample covariance on 3x2pt analysis with Euclid

Author: Euclid Collaboration, Sciotti, D., Beauchamps, S. Gouyou, Cardone, V. F., Camera, S., Tutusaus, I., Lacasa, F., Barreira, A., Gorce, A., Aubert, M., Baratta, P., Upham, R. E., Bonici, M., Carbone, C., Casas, S., Ilić, S., Martinelli, M., Sakr, Z., Schneider, A., Maoli, R., Scaramella, R., Escoffier, S., Gillard, W., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mauri, N., Neissner, C., Scottez, V., Tenti, M., Akrami, Y., Allevato, V., Baccigalupi, C., Ballardini, M., Bernardeau, F., Blanchard, A., Borgani, S., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., {n}as-Herrera, G. Ca\, Chambers, K. C., Cooray, A. R., Coupon, J., Díaz-Sánchez, A., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Vigo, J. A. Escartin, Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Jacobson, J., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mainetti, G., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Pöntinen, M., Patrizii, L., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Sánchez, A. G., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Teyssier, R., Toft, S., Tucci, M., Valieri, C., Valiviita, J., and Viel, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Deviations from Gaussianity in the distribution of the fields probed by large-scale structure surveys generate additional terms in the data covariance matrix, increasing the uncertainties in the measurement of the cosmological parameters. Super-sample covariance (SSC) is among the largest of these non-Gaussian contributions, with the potential to significantly degrade constraints on some of the parameters of the cosmological model under study -- especially for weak lensing cosmic shear. We compute and validate the impact of SSC on the forecast uncertainties on the cosmological parameters for the Euclid photometric survey, obtained with a Fisher matrix analysis, both considering the Gaussian covariance alone and adding the SSC term -- computed through the public code PySSC. The photometric probes are considered in isolation and combined in the `3$\times$2pt' analysis. We find the SSC impact to be non-negligible -- halving the Figure of Merit of the dark energy parameters ($w_0$, $w_a$) in the 3$\times$2pt case and substantially increasing the uncertainties on $\Omega_{{\rm m},0}, w_0$, and $\sigma_8$ for cosmic shear; photometric galaxy clustering, on the other hand, is less affected due to the lower probe response. The relative impact of SSC does not show significant changes under variations of the redshift binning scheme, while it is smaller for weak lensing when marginalising over the multiplicative shear bias nuisance parameters, which also leads to poorer constraints on the cosmological parameters. Finally, we explore how the use of prior information on the shear and galaxy bias changes the SSC impact. Improving shear bias priors does not have a significant impact, while galaxy bias must be calibrated to sub-percent level to increase the Figure of Merit by the large amount needed to achieve the value when SSC is not included., Comment: 22 pages, 13 figures
Published: 2023

35. Euclid preparation. XXXI. The effect of the variations in photometric passbands on photometric-redshift accuracy

Author: Euclid Collaboration, Paltani, Stéphane, Coupon, J., Hartley, W. G., Alvarez-Ayllon, A., Dubath, F., Mohr, J. J., Schirmer, M., Cuillandre, J. -C., Desprez, G., Ilbert, O., Kuijken, K., Aghanim, N., Altieri, B., Amara, A., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Douspis, M., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Haugan, S. V., Hoekstra, H., Hornstrup, A., Hudelot, P., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Masters, D. C., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J., Padilla, C., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. -L., Surace, C., Tallada-Crespí, P., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Aussel, H., Bardelli, S., Bolzonella, M., Boucaud, A., Di Ferdinando, D., Farina, M., Graciá-Carpio, J., Lindholm, V., Maino, D., Mauri, N., Neissner, C., Scottez, V., Zucca, E., Baccigalupi, C., Ballardini, M., Biviano, A., Blanchard, A., Borgani, S., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Chambers, K., Cooray, A. R., Courtois, H. M., Cucciati, O., Davini, S., De Lucia, G., Dole, H., Escartin, J. A., Escoffier, S., Finelli, F., Fotopoulou, S., Ganga, K., George, K., Gozaliasl, G., Hildebrandt, H., Hook, I., Muñoz, A. Jimenez, Joachimi, B., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Pollack, J. E., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Pozzetti, L., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Sefusatti, E., Sereno, M., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Teyssier, R., Valieri, C., Valiviita, J., van Mierlo, S. E., Veropalumbo, A., Viel, M., and Weaver, J. R.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The technique of photometric redshifts has become essential for the exploitation of multi-band extragalactic surveys. While the requirements on photo-zs for the study of galaxy evolution mostly pertain to the precision and to the fraction of outliers, the most stringent requirement in their use in cosmology is on the accuracy, with a level of bias at the sub-percent level for the Euclid cosmology mission. A separate, and challenging, calibration process is needed to control the bias at this level of accuracy. The bias in photo-zs has several distinct origins that may not always be easily overcome. We identify here one source of bias linked to the spatial or time variability of the passbands used to determine the photometric colours of galaxies. We first quantified the effect as observed on several well-known photometric cameras, and found in particular that, due to the properties of optical filters, the redshifts of off-axis sources are usually overestimated. We show using simple simulations that the detailed and complex changes in the shape can be mostly ignored and that it is sufficient to know the mean wavelength of the passbands of each photometric observation to correct almost exactly for this bias; the key point is that this mean wavelength is independent of the spectral energy distribution of the source}. We use this property to propose a correction that can be computationally efficiently implemented in some photo-z algorithms, in particular template-fitting. We verified that our algorithm, implemented in the new photo-z code Phosphoros, can effectively reduce the bias in photo-zs on real data using the CFHTLS T007 survey, with an average measured bias Delta z over the redshift range 0.4
Published: 2023
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36. Euclid preparation. XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear

Author: Euclid Collaboration, Tanidis, K., Cardone, V. F., Martinelli, M., Tutusaus, I., Camera, S., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., DaSilva, A., Degaudenzi, H., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hornstrup, A., Jahnke, K., Joachimi, B., Keihanen, E., Kermiche, S., Kiessling, A., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Pollack, J. E., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Marcin, S., Mauri, N., Scottez, V., Tenti, M., Tramacere, A., Akrami, Y., Allevato, V., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Benielli, D., Bernardeau, F., Borgani, S., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Díaz-Sánchez, A., Davini, S., delaTorre, S., DeLucia, G., Desprez, G., DiDomizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferreira, P. G., Ferrero, I., Finelli, F., Gabarra, L., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Ilić, S., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mainetti, G., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Pöntinen, M., Patrizii, L., Pezzotta, A., Popa, V., Potter, D., Sánchez, A. G., Sakr, Z., Schewtschenko, J. A., Schneider, A., Sereno, M., Simon, P., Mancini, A. Spurio, Steinwagner, J., Tewes, M., Teyssier, R., Toft, S., Valiviita, J., Viel, M., and Linke, L.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Universe. This will allow us to test the concordance cosmological model and its extensions. However, precision pushes us to high levels of accuracy in the theoretical modelling of the LSS observables, so that no biases are introduced into the estimation of the cosmological parameters. In particular, effects such as redshift-space distortions (RSD) can become relevant in the computation of harmonic-space power spectra even for the clustering of the photometrically selected galaxies, as has previously been shown in literature. In this work, we investigate the contribution of linear RSD, as formulated in the Limber approximation by a previous work, in forecast cosmological analyses with the photometric galaxy sample of the Euclid survey. We aim to assess their impact and to quantify the bias on the measurement of cosmological parameters that would be caused if this effect were neglected. We performed this task by producing mock power spectra for photometric galaxy clustering and weak lensing, as is expected to be obtained from the Euclid survey. We then used a Markov chain Monte Carlo approach to obtain the posterior distributions of cosmological parameters from these simulated observations. When the linear RSD is neglected, significant biases are caused when galaxy correlations are used alone and when they are combined with cosmic shear in the so-called 3$\times$2pt approach. These biases can be equivalent to as much as $5\,\sigma$ when an underlying $\Lambda$CDM cosmology is assumed. When the cosmological model is extended to include the equation-of-state parameters of dark energy, the extension parameters can be shifted by more than $1\,\sigma$., Comment: 15 pages, 6 figures. Version matching publication at journal
Published: 2023
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37. Euclid Preparation XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong lensing events

Author: Euclid Collaboration, Leuzzi, L., Meneghetti, M., Angora, G., Metcalf, R. B., Moscardini, L., Rosati, P., Bergamini, P., Calura, F., Clément, B., Gavazzi, R., Gentile, F., Lochner, M., Grillo, C., Vernardos, G., Aghanim, N., Amara, A., Amendola, L., Andreon, S., Auricchio, N., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Joachimi, B., Kümmel, M., Keihänen, E., Kermiche, S., Kiessling, A., Kitching, T., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Merlin, E., Meylan, G., Moresco, M., Munari, E., Niemi, S. -M., Nightingale, J. W., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Boucaud, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mauri, N., Neissner, C., Scottez, V., Tenti, M., Tramacere, A., Akrami, Y., Allevato, V., Baccigalupi, C., Ballardini, M., Bernardeau, F., Biviano, A., Borgani, S., Borlaff, A. S., Bretonnière, H., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Gabarra, L., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., George, K., Gozaliasl, G., Hildebrandt, H., Huertas-Company, M., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Magliocchetti, M., Mainetti, G., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maurin, L., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Pöntinen, M., Patrizii, L., Popa, V., Porciani, C., Potter, D., Reimberg, P., Sánchez, A. G., Sakr, Z., Schneider, A., Sereno, M., Simon, P., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Teyssier, R., Valiviita, J., Viel, M., Zinchenko, I. A., and Sánchez, H. Domínguez
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential candidates. In this context, deep learning techniques are particularly suitable for the finding patterns in large data sets, and convolutional neural networks (CNNs) in particular can efficiently process large volumes of images. We assess and compare the performance of three network architectures in the classification of strong lensing systems on the basis of their morphological characteristics. We train and test our models on different subsamples of a data set of forty thousand mock images, having characteristics similar to those expected in the wide survey planned with the ESA mission \Euclid, gradually including larger fractions of faint lenses. We also evaluate the importance of adding information about the colour difference between the lens and source galaxies by repeating the same training on single-band and multi-band images. Our models find samples of clear lenses with $\gtrsim 90\%$ precision and completeness, without significant differences in the performance of the three architectures. Nevertheless, when including lenses with fainter arcs in the training set, the three models' performance deteriorates with accuracy values of $\sim 0.87$ to $\sim 0.75$ depending on the model. Our analysis confirms the potential of the application of CNNs to the identification of galaxy-scale strong lenses. We suggest that specific training with separate classes of lenses might be needed for detecting the faint lenses since the addition of the colour information does not yield a significant improvement in the current analysis, with the accuracy ranging from $\sim 0.89$ to $\sim 0.78$ for the different models., Comment: 23 pages,12 figures
Published: 2023
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38. Euclid preparation. XXIX. Water ice in spacecraft part I: The physics of ice formation and contamination

Author: Euclid Collaboration, Schirmer, M., Thürmer, K., Bras, B., Cropper, M., Martin-Fleitas, J., Goueffon, Y., Kohley, R., Mora, A., Portaluppi, M., Racca, G. D., Short, A. D., Szmolka, S., Venancio, L. M. Gaspar, Altmann, M., Balog, Z., Bastian, U., Biermann, M., Busonero, D., Fabricius, C., Grupp, F., Jordi, C., Löffler, W., Sellés, A. Sagristà, Aghanim, N., Amara, A., Amendola, L., Baldi, M., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. -M., Nightingale, J. W., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zacchei, A., Zoubian, J., Andreon, S., Bardelli, S., Battaglia, P., Bozzo, E., Colodro-Conde, C., Farina, M., Graciá-Carpio, J., Keihänen, E., Lindholm, V., Maino, D., Mauri, N., Morisset, N., Scottez, V., Tenti, M., Zucca, E., Akrami, Y., Baccigalupi, C., Ballardini, M., Biviano, A., Blanchard, A., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Castro, T., Chambers, K. C., Cooray, A. R., Coupon, J., Courtois, H. M., Cuby, J. -G., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Escartin, J. A., Escoffier, S., Ferrero, I., Gabarra, L., Ganga, K., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Liebing, P., Loureiro, A., Maggio, G., Magliocchetti, M., Mainetti, G., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Pollack, J. E., Popa, V., Potter, D., Pöntinen, M., Sánchez, A. G., Sakr, Z., Schneider, A., Sereno, M., Shulevski, A., Simon, P., Steinwagner, J., Teyssier, R., and Valiviita, J.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Molecular contamination is a well-known problem in space flight. Water is the most common contaminant and alters numerous properties of a cryogenic optical system. Too much ice means that Euclid's calibration requirements and science goals cannot be met. Euclid must then be thermally decontaminated, a long and risky process. We need to understand how iced optics affect the data and when a decontamination is required. This is essential to build adequate calibration and survey plans, yet a comprehensive analysis in the context of an astrophysical space survey has not been done before. In this paper we look at other spacecraft with well-documented outgassing records, and we review the formation of thin ice films. A mix of amorphous and crystalline ices is expected for Euclid. Their surface topography depends on the competing energetic needs of the substrate-water and the water-water interfaces, and is hard to predict with current theories. We illustrate that with scanning-tunnelling and atomic-force microscope images. Industrial tools exist to estimate contamination, and we must understand their uncertainties. We find considerable knowledge errors on the diffusion and sublimation coefficients, limiting the accuracy of these tools. We developed a water transport model to compute contamination rates in Euclid, and find general agreement with industry estimates. Tests of the Euclid flight hardware in space simulators did not pick up contamination signals; our in-flight calibrations observations will be much more sensitive. We must understand the link between the amount of ice on the optics and its effect on Euclid's data. Little research is available about this link, possibly because other spacecraft can decontaminate easily, quenching the need for a deeper understanding. In our second paper we quantify the various effects of iced optics on spectrophotometric data., Comment: 35 pages, 22 figures, A&A in press. Changes to previous version: language edits, added Z. Bolag as author in the arxiv PDF (was listed in the ASCII author list and in the journal PDF, but not in the arxiv PDF). This version is identical to the journal version
Published: 2023
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39. Euclid preparation. XXVII. A UV-NIR spectral atlas of compact planetary nebulae for wavelength calibration

Author: Euclid Collaboration, Paterson, K., Schirmer, M., Copin, Y., Cuillandre, J. -C., Gillard, W., Soto, L. A. Gutiérrez, Guzzo, L., Hoekstra, H., Kitching, T., Paltani, S., Percival, W. J., Scodeggio, M., Stanghellini, L., Appleton, P. N., Laureijs, R., Mellier, Y., Aghanim, N., Altieri, B., Amara, A., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Corcione, L., Courbin, F., Da Silva, A., Degaudenzi, H., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hornstrup, A., Hudelot, P., Jahnke, K., Kümmel, M., Kiessling, A., Kilbinger, M., Kohley, R., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Nakajima, R., Niemi, S. -M., Nightingale, J. W., Nutma, T., Padilla, C., Pasian, F., Pedersen, K., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Rix, H. -W., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Farina, M., Graciá-Carpio, J., Keihänen, E., Lindholm, V., Maino, D., Mauri, N., Scottez, V., Tenti, M., Zucca, E., Akrami, Y., Baccigalupi, C., Ballardini, M., Biviano, A., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Castro, T., Chambers, K. C., Cooray, A. R., Coupon, J., Courtois, H. M., Davini, S., De Lucia, G., Desprez, G., Escartin, J. A., Escoffier, S., Ferrero, I., Gabarra, L., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Hook, I., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Magliocchetti, M., Mainetti, G., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Pollack, J., Porciani, C., Potter, D., Pöntinen, M., Sánchez, A. G., Sakr, Z., Schneider, A., Sefusatti, E., Sereno, M., Shulevski, A., Stadel, J., Steinwagner, J., Valieri, C., Valiviita, J., Veropalumbo, A., Viel, M., and Zinchenko, I. A.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract: The Euclid mission will conduct an extragalactic survey over 15000 deg$^2$ of the extragalactic sky. The spectroscopic channel of the Near-Infrared Spectrometer and Photometer (NISP) has a resolution of $R\sim450$ for its blue and red grisms that collectively cover the $0.93$--$1.89 $\micron;range. NISP will obtain spectroscopic redshifts for $3\times10^7$ galaxies for the experiments on galaxy clustering, baryonic acoustic oscillations, and redshift space distortion. The wavelength calibration must be accurate within $5$\AA to avoid systematics in the redshifts and downstream cosmological parameters. The NISP pre-flight dispersion laws for the grisms were obtained on the ground using a Fabry-Perot etalon. Launch vibrations, zero gravity conditions, and thermal stabilisation may alter these dispersion laws, requiring an in-flight recalibration. To this end, we use the emission lines in the spectra of compact planetary nebulae (PNe), which were selected from a PN data base. To ensure completeness of the PN sample, we developed a novel technique to identify compact and strong line emitters in Gaia spectroscopic data using the Gaia spectra shape coefficients. We obtained VLT/X-SHOOTER spectra from $0.3$ to $2.5$ \micron;for 19 PNe in excellent seeing conditions and a wide slit, mimicking Euclid's slitless spectroscopy mode but with 10 times higher spectral resolution. Additional observations of one northern PN were obtained in the $0.80$--$1.90$ \micron range with the GMOS and GNIRS instruments at the Gemini North observatory. The collected spectra were combined into an atlas of heliocentric vacuum wavelengths with a joint statistical and systematic accuracy of 0.1 \AA in the optical and 0.3 \AA in the near-infrared. The wavelength atlas and the related 1D and 2D spectra are made publicly available., Comment: Accepted in A&A
Published: 2023
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40. Euclid preparation. XXX. Performance assessment of the NISP Red-Grism through spectroscopic simulations for the Wide and Deep surveys

Author: Euclid Collaboration, Gabarra, L., Mancini, C., Munoz, L. Rodriguez, Rodighiero, G., Sirignano, C., Scodeggio, M., Talia, M., Dusini, S., Gillard, W., Granett, B. R., Maiorano, E., Moresco, M., Paganin, L., Palazzi, E., Pozzetti, L., Renzi, A., Rossetti, E., Vergani, D., Allevato, V., Bisigello, L., Castignani, G., De Caro, B., Fumana, M., Ganga, K., Garilli, B., Hirschmann, M., La Franca, F., Laigle, C., Passalacqua, F., Schirmer, M., Stanco, L., Troja, A., Yung, L. Y. A., Zamorani, G., Zoubian, J., Aghanim, N., Amara, A., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Costille, A., Courbin, F., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., Dupac, X., Ealet, A., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Holmes, W., Hornstrup, A., Hudelot, P., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., Mei, S., Meneghetti, M., Meylan, G., Moscardini, L., Munari, E., Nichol, R. C., Niemi, S. -M., Nightingale, J., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Raison, F., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sapone, D., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirri, G., Surace, C., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Trifoglio, M., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zacchei, A., Andreon, S., Aussel, H., Bardelli, S., Bolzonella, M., Boucaud, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Farina, M., Graciá-Carpio, J., Keihänen, E., Lindholm, V., Maino, D., Mauri, N., Mellier, Y., Neissner, C., Scottez, V., Tenti, M., Zucca, E., Akrami, Y., Baccigalupi, C., Ballardini, M., Bernardeau, F., Biviano, A., Borlaff, A. S., Borsato, E., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castro, T., Chambers, K., Cooray, A. R., Coupon, J., Courtois, H. M., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Ferrero, I., Finelli, F., Fotopoulou, S., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Hook, I., Ilbert, O., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mainetti, G., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Sánchez, A. G., Sakr, Z., Schneider, A., Sefusatti, E., Sereno, M., Shulevski, A., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Teyssier, R., Valiviita, J., Veropalumbo, A., Viel, M., and Zinchenko, I. A.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: This work focuses on the pilot run of a simulation campaign aimed at investigating the spectroscopic capabilities of the Euclid Near-Infrared Spectrometer and Photometer (NISP), in terms of continuum and emission line detection in the context of galaxy evolutionary studies. To this purpose we constructed, emulated, and analysed the spectra of 4992 star-forming galaxies at $0.3 \leq z \leq 2.5$ using the NISP pixel-level simulator. We built the spectral library starting from public multi-wavelength galaxy catalogues, with value-added information on spectral energy distribution (SED) fitting results, and from Bruzual and Charlot (2003) stellar population templates. Rest-frame optical and near-IR nebular emission lines were included using empirical and theoretical relations. We inferred the 3.5$\sigma$ NISP red grism spectroscopic detection limit of the continuum measured in the $H$ band for star-forming galaxies with a median disk half-light radius of \ang{;;0.4} at magnitude $H= 19.5\pm0.2\,$AB$\,$mag for the Euclid Wide Survey and at $H = 20.8\pm0.6\,$AB$\,$mag for the Euclid Deep Survey. We found a very good agreement with the red grism emission line detection limit requirement for the Wide and Deep surveys. We characterised the effect of the galaxy shape on the detection capability of the red grism and highlighted the degradation of the quality of the extracted spectra as the disk size increases. In particular, we found that the extracted emission line signal to noise ratio (SNR) drops by $\sim\,$45$\%$ when the disk size ranges from \ang{;;0.25} to \ang{;;1}. These trends lead to a correlation between the emission line SNR and the stellar mass of the galaxy and we demonstrate the effect in a stacking analysis unveiling emission lines otherwise too faint to detect., Comment: 24 pages, 21 figures
Published: 2023
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41. Euclid preparation: XXVIII. Modelling of the weak lensing angular power spectrum

Author: Euclid Collaboration, Deshpande, A. C., Kitching, T., Hall, A., Brown, M. L., Aghanim, N., Amendola, L., Auricchio, N., Baldi, M., Bender, R., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hornstrup, A., Hudelot, P., Jahnke, K., Kermiche, S., Kilbinger, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Mei, S., Mellier, Y., Meneghetti, M., Meylan, G., Moscardini, L., Niemi, S. -M., Nightingale, J. W., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespi, P., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Boucaud, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Fabbian, G., Farina, M., Gracia-Carpio, J., Keihanen, E., Lindholm, V., Mauri, N., Scottez, V., Tenti, M., Zucca, E., Akrami, Y., Baccigalupi, C., Balaguera-Antolinez, A., Ballardini, M., Bernardeau, F., Biviano, A., Blanchard, A., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Castro, T., Chambers, K. C., Cooray, A. R., Coupon, J., Courtois, H. M., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Ferrero, I., Finelli, F., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mainetti, G., Maoli, R., Martinelli, M., Martinet, N., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Peel, A., Pollack, J., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Pontinen, M., Reimberg, P., Sanchez, A. G., Sakr, Z., Schneider, A., Sefusatti, E., Sereno, M., Shulevski, A., Mancini, A. Spurio, Steinwagner, J., Teyssier, R., Viel, M., and Zinchenko, I. A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: This work considers which higher-order effects in modelling the cosmic shear angular power spectra must be taken into account for Euclid. We identify which terms are of concern, and quantify their individual and cumulative impact on cosmological parameter inference from Euclid. We compute the values of these higher-order effects using analytic expressions, and calculate the impact on cosmological parameter estimation using the Fisher matrix formalism. We review 24 effects and find the following potentially need to be accounted for: the reduced shear approximation, magnification bias, source-lens clustering, source obscuration, local Universe effects, and the flat Universe assumption. Upon computing these explicitly, and calculating their cosmological parameter biases, using a maximum multipole of $\ell=5000$, we find that the magnification bias, source-lens clustering, source obscuration, and local Universe terms individually produce significant ($\,>0.25\sigma$) cosmological biases in one or more parameters, and accordingly must be accounted for. In total, over all effects, we find biases in $\Omega_{\rm m}$, $\Omega_{\rm b}$, $h$, and $\sigma_{8}$ of $0.73\sigma$, $0.28\sigma$, $0.25\sigma$, and $-0.79\sigma$, respectively, for flat $\Lambda$CDM. For the $w_0w_a$CDM case, we find biases in $\Omega_{\rm m}$, $\Omega_{\rm b}$, $h$, $n_{\rm s}$, $\sigma_{8}$, and $w_a$ of $1.49\sigma$, $0.35\sigma$, $-1.36\sigma$, $1.31\sigma$, $-0.84\sigma$, and $-0.35\sigma$, respectively; which are increased relative to the $\Lambda$CDM due to additional degeneracies as a function of redshift and scale., Comment: 20 pages, submitted to A&A
Published: 2023

42. Euclid Preparation. XXVIII. Forecasts for ten different higher-order weak lensing statistics

Author: Euclid Collaboration, Ajani, V., Baldi, M., Barthelemy, A., Boyle, A., Burger, P., Cardone, V. F., Cheng, S., Codis, S., Giocoli, C., Harnois-Déraps, J., Heydenreich, S., Kansal, V., Kilbinger, M., Linke, L., Llinares, C., Martinet, N., Parroni, C., Peel, A., Pires, S., Porth, L., Tereno, I., Uhlemann, C., Vicinanza, M., Vinciguerra, S., Aghanim, N., Auricchio, N., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillis, B., Grazian, A., Grupp, F., Hoekstra, H., Holmes, W., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Kümmel, M., Kitching, T., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Mei, S., Mellier, Y., Meneghetti, M., Moresco, M., Moscardini, L., Niemi, S. -M., Nightingale, J., Nutma, T., Padilla, C., Paltani, S., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Boucaud, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Fabbian, G., Farina, M., Graciá-Carpio, J., Keihänen, E., Lindholm, V., Maino, D., Mauri, N., Neissner, C., Schirmer, M., Scottez, V., Zucca, E., Akrami, Y., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Bernardeau, F., Biviano, A., Blanchard, A., Borgani, S., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Castro, T., Chambers, K. C., Cooray, A. R., Coupon, J., Courtois, H. M., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Ferrero, I., Finelli, F., Ganga, K., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Muñoz, A. Jimenez, Joachimi, B., Kajava, J. J. E., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Magliocchetti, M., Maoli, R., Marcin, S., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Popa, V., Potter, D., Pourtsidou, A., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Schneider, A., Sefusatti, E., Sereno, M., Shulevski, A., Mancini, A. Spurio, Steinwagner, J., Teyssier, R., Valiviita, J., Veropalumbo, A., Viel, M., and Zinchenko, I. A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of $Euclid$-like mocks, derived from N-body simulations. In this first paper of the HOWLS series, we computed the nontomographic ($\Omega_{\rm m}$, $\sigma_8$) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a $4.5$ times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with $Euclid$. The data used in this analysis are publicly released with the paper., Comment: 33 pages, 24 figures, main results in Fig. 19 & Table 5, version published in A&A
Published: 2023
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43. Euclid preparation: XXII. Selection of Quiescent Galaxies from Mock Photometry using Machine Learning

Author: Euclid Collaboration, Humphrey, A., Bisigello, L., Cunha, P. A. C., Bolzonella, M., Fotopoulou, S., Caputi, K., Tortora, C., Zamorani, G., Papaderos, P., Vergani, D., Brinchmann, J., Moresco, M., Amara, A., Auricchio, N., Baldi, M., Bender, R., Bonino, D., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Gomez-Alvarez, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Jahnke, K., Kummel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. M., Nightingale, J., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Scaramella, R., Schneider, P., Scodeggio, M., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespi, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zacchei, A., Zoubian, J., Andreon, S., Bardelli, S., Boucaud, A., Farinelli, R., Gracia-Carpio, J., Maino, D., Mauri, N., Mei, S., Morisset, N., Sureau, F., Tenti, M., Tramacere, A., Zucca, E., Baccigalupi, C., Balaguera-Antolinez, A., Biviano, A., Blanchard, A., Borgani, S., Bozzo, E., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Colodro-Conde, C., Cooray, A. R., Coupon, J., Courtois, H. M., Cucciati, O., Davini, S., De Lucia, G., Dole, H., Escartin, J. A., Escoffier, S., Fabricius, M., Farina, M., Finelli, F., Ganga, K., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hook, I., Huertas-Company, M., Joachimi, B., Kansal, V., Kashlinsky, A., Keihanen, E., Kirkpatrick, C. C., Lindholm, V., Mainetti, G., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Maturi, M., Metcalf, R. B., Morgante, G., Nucita, A. A., Patrizii, L., Peel, A., Pollack, J. E., Popa, V., Porciani, C., Potter, D., Reimberg, P., Sanchez, A. G., Schirmer, M., Schultheis, M., Scottez, V., Sefusatti, E., Stadel, J., Teyssier, R., Valieri, C., Valiviita, J., Viel, M., Calura, F., and Hildebrandt, H.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across ~15,000 sq deg of the sky. Euclid is expected to detect ~12 billion astronomical sources, facilitating new insights into cosmology, galaxy evolution, and various other topics. To optimally exploit the expected very large data set, there is the need to develop appropriate methods and software. Here we present a novel machine-learning based methodology for selection of quiescent galaxies using broad-band Euclid I_E, Y_E, J_E, H_E photometry, in combination with multiwavelength photometry from other surveys. The ARIADNE pipeline uses meta-learning to fuse decision-tree ensembles, nearest-neighbours, and deep-learning methods into a single classifier that yields significantly higher accuracy than any of the individual learning methods separately. The pipeline has `sparsity-awareness', so that missing photometry values are still informative for the classification. Our pipeline derives photometric redshifts for galaxies selected as quiescent, aided by the `pseudo-labelling' semi-supervised method. After application of the outlier filter, our pipeline achieves a normalized mean absolute deviation of ~< 0.03 and a fraction of catastrophic outliers of ~< 0.02 when measured against the COSMOS2015 photometric redshifts. We apply our classification pipeline to mock galaxy photometry catalogues corresponding to three main scenarios: (i) Euclid Deep Survey with ancillary ugriz, WISE, and radio data; (ii) Euclid Wide Survey with ancillary ugriz, WISE, and radio data; (iii) Euclid Wide Survey only. Our classification pipeline outperforms UVJ selection, in addition to the Euclid I_E-Y_E, J_E-H_E and u-I_E,I_E-J_E colour-colour methods, with improvements in completeness and the F1-score of up to a factor of 2. (Abridged), Comment: 37 pages (including appendices), 26 figures; accepted for publication in Astronomy & Astrophysics
Published: 2022
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44. Euclid preparation XXVI. The Euclid Morphology Challenge. Towards structural parameters for billions of galaxies

Author: Euclid Collaboration, Bretonnière, H., Kuchner, U., Huertas-Company, M., Merlin, E., Castellano, M., Tuccillo, D., Buitrago, F., Conselice, C. J., Boucaud, A., Häußler, B., Kümmel, M., Hartley, W. G., Ayllon, A. Alvarez, Bertin, E., Ferrari, F., Ferreira, L., Gavazzi, R., Hernández-Lang, D., Lucatelli, G., Robotham, A. S. G., Schefer, M., Wang, L., Cabanac, R., Sánchez, H. Domínguez, Duc, P. -A., Fotopoulou, S., Kruk, S., La Marca, A., Margalef-Bentabol, B., Marleau, F. R., Tortora, C., Aghanim, N., Amara, A., Auricchio, N., Azzollini, R., Baldi, M., Bender, R., Bodendorf, C., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Kermiche, S., Kiessling, A., Kohley, R., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., McCracken, H. J., Medinaceli, E., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W., Pettorino, V., Polenta, G., Poncet, M., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Rosset, C., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Skottfelt, J., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Lindholm, V., Mauri, N., Mei, S., Scottez, V., Zucca, E., Baccigalupi, C., Ballardini, M., Bernardeau, F., Biviano, A., Borgani, S., Borlaff, A. S., Burigana, C., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Cooray, A. R., Coupon, J., Courtois, H. M., Davini, S., De Lucia, G., Desprez, G., Escartin, J. A., Escoffier, S., Fabricius, M., Farina, M., Fontana, A., Ganga, K., Garcia-Bellido, J., George, K., Gozaliasl, G., Hildebrandt, H., Hook, I., Ilbert, O., Ilić, S., Joachimi, B., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Maturi, M., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Schirmer, M., Sefusatti, E., Sereno, M., Stadel, J., Teyssier, R., Valiviita, J., van Mierlo, S. E., Veropalumbo, A., Viel, M., Weaver, J. R., and Scott, D.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15 000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morphologies from Euclid-detected galaxies and to help implement measurements in the pipeline, we have conducted the Euclid Morphology Challenge, which we present in two papers. While the companion paper by Merlin et al. focuses on the analysis of photometry, this paper assesses the accuracy of the parametric galaxy morphology measurements in imaging predicted from within the Euclid Wide Survey. We evaluate the performance of five state-of-the-art surface-brightness-fitting codes DeepLeGATo, Galapagos-2, Morfometryka, Profit and SourceXtractor++ on a sample of about 1.5 million simulated galaxies resembling reduced observations with the Euclid VIS and NIR instruments. The simulations include analytic S\'ersic profiles with one and two components, as well as more realistic galaxies generated with neural networks. We find that, despite some code-specific differences, all methods tend to achieve reliable structural measurements (10% scatter on ideal S\'ersic simulations) down to an apparent magnitude of about 23 in one component and 21 in two components, which correspond to a signal-to-noise ratio of approximately 1 and 5 respectively. We also show that when tested on non-analytic profiles, the results are typically degraded by a factor of 3, driven by systematics. We conclude that the Euclid official Data Releases will deliver robust structural parameters for at least 400 million galaxies in the Euclid Wide Survey by the end of the mission. We find that a key factor for explaining the different behaviour of the codes at the faint end is the set of adopted priors for the various structural parameters., Comment: Accepted by A&A. 30 pages, 23+6 figures, Euclid pre-launch key paper. Companion paper: Euclid Collaboration XXV: Merlin et al. 2022 Minor corrections after journal review
Published: 2022
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45. Euclid preparation. XXV. The Euclid Morphology Challenge -- Towards model-fitting photometry for billions of galaxies

Author: Euclid Collaboration, Merlin, E., Castellano, M., Bretonnière, H., Huertas-Company, M., Kuchner, U., Tuccillo, D., Buitrago, F., Peterson, J. R., Conselice, C. J., Caro, F., Dimauro, P., Nemani, L., Fontana, A., Kümmel, M., Häußler, B., Hartley, W. G., Ayllon, A. Alvarez, Bertin, E., Dubath, P., Ferrari, F., Ferreira, L., Gavazzi, R., Hernández-Lang, D., Lucatelli, G., Robotham, A. S. G., Schefer, M., Tortora, C., Aghanim, N., Amara, A., Amendola, L., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Kermiche, S., Kiessling, A., Kitching, T., Kohley, R., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., McCracken, H. J, Medinaceli, E., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Polenta, G., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Skottfelt, J., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Boucaud, A., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Lindholm, V., Mauri, N., Mei, S., Neissner, C., Scottez, V., Tramacere, A., Zucca, E., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Bernardeau, F., Biviano, A., Borgani, S., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Cooray, A. R., Coupon, J., Courtois, H. M., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Escartin, J. A., Escoffier, S., Farina, M., Ganga, K., Garcia-Bellido, J., George, K., Gozaliasl, G., Hildebrandt, H., Hook, I., Ilbert, O., Ilic, S., Joachimi, B., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mainetti, G., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Matthew, S., Maturi, M., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Schirmer, M., Sereno, M., Stadel, J., Teyssier, R., Valieri, C., Valiviita, J., van Mierlo, S. E., Veropalumbo, A., Viel, M., Weaver, J. R., and Scott, D.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The ESA Euclid mission will provide high-quality imaging for about 1.5 billion galaxies. A software pipeline to automatically process and analyse such a huge amount of data in real time is being developed by the Science Ground Segment of the Euclid Consortium; this pipeline will include a model-fitting algorithm, which will provide photometric and morphological estimates of paramount importance for the core science goals of the mission and for legacy science. The Euclid Morphology Challenge is a comparative investigation of the performance of five model-fitting software packages on simulated Euclid data, aimed at providing the baseline to identify the best suited algorithm to be implemented in the pipeline. In this paper we describe the simulated data set, and we discuss the photometry results. A companion paper (Euclid Collaboration: Bretonni\`ere et al. 2022) is focused on the structural and morphological estimates. We created mock Euclid images simulating five fields of view of 0.48 deg2 each in the $I_E$ band of the VIS instrument, each with three realisations of galaxy profiles (single and double S\'ersic, and 'realistic' profiles obtained with a neural network); for one of the fields in the double S\'ersic realisation, we also simulated images for the three near-infrared $Y_E$, $J_E$ and $H_E$ bands of the NISP-P instrument, and five Rubin/LSST optical complementary bands ($u$, $g$, $r$, $i$, and $z$). To analyse the results we created diagnostic plots and defined ad-hoc metrics. Five model-fitting software packages (DeepLeGATo, Galapagos-2, Morfometryka, ProFit, and SourceXtractor++) were compared, all typically providing good results. (cut), Comment: 29 pages, 33 figures. Euclid pre-launch key paper. Companion paper: Bretonniere et al. 2022
Published: 2022
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46. Euclid preparation. XXIV. Calibration of the halo mass function in $\Lambda(\nu)$CDM cosmologies

Author: Euclid Collaboration, Castro, T., Fumagalli, A., Angulo, R. E., Bocquet, S., Borgani, S., Carbone, C., Dakin, J., Dolag, K., Giocoli, C., Monaco, P., Ragagnin, A., Saro, A., Sefusatti, E., Costanzi, M., Brun, A. M. C. Le, Corasaniti, P. -S., Amara, A., Amendola, L., Baldi, M., Bender, R., Bodendorf, C., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillis, B., Grazian, A., Grupp, F., Haugan, S. V. H., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Kermiche, S., Kitching, T., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Marulli, F., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Seidel, G., Sirri, G., Stanco, L., Crespí, P. Tallada, Taylor, A. N., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Andreon, S., Bardelli, S., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Farina, M., Graciá-Carpio, J., Lindholm, V., Neissner, C., Scottez, V., Tenti, M., Zucca, E., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Bernardeau, F., Biviano, A., Blanchard, A., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Cooray, A., Coupon, J., Courtois, H. M., Davini, S., De Lucia, G., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Finelli, F., Ganga, K., Garcia-Bellido, J., George, K., Gozaliasl, G., Hildebrandt, H., Hook, I., Ilić, S., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Matthew, S., Maturi, M., Metcalf, R. B., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Peel, A., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Pöntinen, M., Sánchez, A. G., Sakr, Z., Schirmer, M., Sereno, M., Mancini, A. Spurio, Teyssier, R., Valiviita, J., Veropalumbo, A., and Viel, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Euclid's photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number count, within which the halo mass function (HMF) is a key theoretical quantity. We present a new calibration of the analytic HMF, at the level of accuracy and precision required for the uncertainty in this quantity to be subdominant with respect to other sources of uncertainty in recovering cosmological parameters from Euclid cluster counts. Our model is calibrated against a suite of N-body simulations using a Bayesian approach taking into account systematic errors arising from numerical effects in the simulation. First, we test the convergence of HMF predictions from different N-body codes, by using initial conditions generated with different orders of Lagrangian Perturbation theory, and adopting different simulation box sizes and mass resolution. Then, we quantify the effect of using different halo-finder algorithms, and how the resulting differences propagate to the cosmological constraints. In order to trace the violation of universality in the HMF, we also analyse simulations based on initial conditions characterised by scale-free power spectra with different spectral indexes, assuming both Einstein--de Sitter and standard $\Lambda$CDM expansion histories. Based on these results, we construct a fitting function for the HMF that we demonstrate to be sub-percent accurate in reproducing results from 9 different variants of the $\Lambda$CDM model including massive neutrinos cosmologies. The calibration systematic uncertainty is largely sub-dominant with respect to the expected precision of future mass-observation relations; with the only notable exception of the effect due to the halo finder, that could lead to biased cosmological inference., Comment: 25 pages, 21 figures, 5 tables, 3 appendixes; v2 matches published version
Published: 2022
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47. Euclid preparation: XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images

Author: Euclid Collaboration, Bisigello, L., Conselice, C. J., Baes, M., Bolzonella, M., Brescia, M., Cavuoti, S., Cucciati, O., Humphrey, A., Hunt, L. K., Maraston, C., Pozzetti, L., Tortora, C., van Mierlo, S. E., Aghanim, N., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Castellano, M., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kohley, R., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Rix, H. -W., Romelli, E., Roncarelli, M., Rosset, C., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Scodeggio, M., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zacchei, A., Zamorani, G., Zoubian, J., Andreon, S., Boucaud, S. Bardelli A., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Lindholm, V., Maino, D., Mei, S., Scottez, V., Sureau, F., Tenti, M., Zucca, E., Borlaff, A. S., Ballardini, M., Biviano, A., Bozzo, E., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Cooray, A., Coupon, J., Courtois, H. M., Cuby, J., Davini, S., De Lucia, G., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Farina, M., Fotopoulou, S., Ganga, K., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Hook, I., Huertas-Company, M., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macías-Pérez, J. F., Magliocchetti, M., Mainetti, G., Marcin, S., Martinelli, M., Martinet, N., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Peel, A., Potter, D., Pourtsidou, A., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Schirmer, M., Sefusatti, E., Sereno, M., Stadel, J., Teyssier, R., Valieri, C., Valiviita, J., and Viel, M.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine learning methods are increasingly becoming the most efficient tools to handle this enormous amount of data, because they are often faster and more accurate than traditional methods. We investigate how well redshifts, stellar masses, and star-formation rates (SFR) can be measured with deep learning algorithms for observed galaxies within data mimicking the Euclid and Rubin/LSST surveys. We find that Deep Learning Neural Networks and Convolutional Neutral Networks (CNN), which are dependent on the parameter space of the training sample, perform well in measuring the properties of these galaxies and have a better accuracy than methods based on spectral energy distribution fitting. CNNs allow the processing of multi-band magnitudes together with $H_{\scriptscriptstyle\rm E}$-band images. We find that the estimates of stellar masses improve with the use of an image, but those of redshift and SFR do not. Our best results are deriving i) the redshift within a normalised error of less than 0.15 for 99.9$\%$ of the galaxies with S/N>3 in the $H_{\scriptscriptstyle\rm E}$-band; ii) the stellar mass within a factor of two ($\sim0.3 \rm dex$) for 99.5$\%$ of the considered galaxies; iii) the SFR within a factor of two ($\sim0.3 \rm dex$) for $\sim$70$\%$ of the sample. We discuss the implications of our work for application to surveys as well as how measurements of these galaxy parameters can be improved with deep learning., Comment: accepted for publication in MNRAS, 21 pages, 22 figures, 6 tables
Published: 2022

48. Euclid preparation: XX. The Complete Calibration of the Color-Redshift Relation survey: LBT observations and data release

Author: Euclid Collaboration, Saglia, R., De Nicola, S., Fabricius, M., Guglielmo, V., Snigula, J., Zöller, R., Bender, R., Heidt, J., Masters, D., Stern, D., Paltani, S., Amara, A., Auricchio, N., Baldi, M., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Marggraf, O., Markovic, K., Marulli, F., Massey, R., McCracken, H. J., Melchior, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Rossetti, E., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zacchei, A., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Graciá-Carpio, J., Maino, D., Mauri, N., Tramacere, A., Zucca, E., Ayllon, A. Alvarez, Aussel, H., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Cooray, A., Coupon, J., Courtois, H. M., Davini, S., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Farina, M., Fotopoulou, S., Ganga, K., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Hook, I., Ilbert, O., Kansal, V., Kashlinsky, A., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macías-Pérez, J., Magliocchetti, M., Mainetti, G., Maoli, R., Martinelli, M., Martinet, N., Metcalf, R. B., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Reimberg, P., Sánchez, A. G., Sakr, Z., Schirmer, M., Sefusatti, E., Sereno, M., Stadel, J., Teyssier, R., Valieri, C., Valiviita, J., Veropalumbo, A., and Viel, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Complete Calibration of the Color-Redshift Relation survey (C3R2) is a spectroscopic programme designed to empirically calibrate the galaxy color-redshift relation to the Euclid depth (I_E=24.5), a key ingredient for the success of Stage IV dark energy projects based on weak lensing cosmology. A spectroscopic calibration sample as representative as possible of the galaxies in the Euclid weak lensing sample is being collected, selecting galaxies from a self-organizing map (SOM) representation of the galaxy color space. Here, we present the results of a near-infrared H- and K-bands spectroscopic campaign carried out using the LUCI instruments at the LBT. For a total of 251 galaxies, we present new highly-reliable redshifts in the 1.3<= z <=1.7 and 2<= z<=2.7 ranges. The newly-determined redshifts populate 49 SOM cells which previously contained no spectroscopic measurements and almost double the occupation numbers of an additional 153 SOM cells. A final optical ground-based observational effort is needed to calibrate the missing cells in particular in the redshift range 1.7<= z<=2.7 that lack spectroscopic calibration. In the end, Euclid itself will deliver telluric-free NIR spectra that can complete the calibration., Comment: A&A language edited version
Published: 2022
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49. Euclid preparation. XXI. Intermediate-redshift contaminants in the search for $z>6$ galaxies within the Euclid Deep Survey

Author: Euclid Collaboration, van Mierlo, S. E., Caputi, K. I., Ashby, M., Atek, H., Bolzonella, M., Bowler, R. A. A., Brammer, G., Conselice, C. J., Cuby, J., Dayal, P., Díaz-Sánchez, A., Finkelstein, S. L., Hoekstra, H., Humphrey, A., Ilbert, O., McCracken, H. J., Milvang-Jensen, B., Oesch, P. A., Pello, R., Rodighiero, G., Schirmer, M., Toft, S., Weaver, J. R., Wilkins, S. M., Willott, C. J., Zamorani, G., Amara, A., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kümmel, M., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zacchei, A., Zoubian, J., Andreon, S., Bardelli, S., Boucaud, A., Graciá-Carpio, J., Maino, D., Mauri, N., Mei, S., Sureau, F., Zucca, E., Aussel, H., Baccigalupi, C., Balaguera-Antolínez, A., Biviano, A., Blanchard, A., Borgani, S., Bozzo, E., Burigana, C., Cabanac, R., Calura, F., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Colodro-Conde, C., Cooray, A. R., Coupon, J., Courtois, H. M., Crocce, M., Cucciati, O., Davini, S., Dole, H., Escartin, J. A., Escoffier, S., Fabricius, M., Farina, M., Ganga, K., García-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Gwyn, S., Hook, I., Huertas-Company, M., Kansal, V., Kashlinsky, A., Keihanen, E., Kirkpatrick, C. C., Lindholm, V., Maoli, R., Martinelli, M., Martinet, N., Maturi, M., Metcalf, R. B., Monaco, P., Morgante, G., Nucita, A. A., Patrizii, L., Peel, A., Pollack, J., Popa, V., Porciani, C., Potter, D., Reimberg, P., Sánchez, A. G., Scottez, V., Sefusatti, E., Stadel, J., Teyssier, R., Valiviita, J., and Viel, M.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: (Abridged) The Euclid mission is expected to discover thousands of z>6 galaxies in three Deep Fields, which together will cover a ~40 deg2 area. However, the limited number of Euclid bands and availability of ancillary data could make the identification of z>6 galaxies challenging. In this work, we assess the degree of contamination by intermediate-redshift galaxies (z=1-5.8) expected for z>6 galaxies within the Euclid Deep Survey. This study is based on ~176,000 real galaxies at z=1-8 in a ~0.7 deg2 area selected from the UltraVISTA ultra-deep survey, and ~96,000 mock galaxies with 25.3$\leq$H<27.0, which altogether cover the range of magnitudes to be probed in the Euclid Deep Survey. We simulate Euclid and ancillary photometry from the fiducial, 28-band photometry, and fit spectral energy distributions (SEDs) to various combinations of these simulated data. Our study demonstrates that identifying z>6 with Euclid data alone will be very effective, with a z>6 recovery of 91(88)% for bright (faint) galaxies. For the UltraVISTA-like bright sample, the percentage of z=1-5.8 contaminants amongst apparent z>6 galaxies as observed with Euclid alone is 18%, which is reduced to 4(13)% by including ultra-deep Rubin (Spitzer) photometry. Conversely, for the faint mock sample, the contamination fraction with Euclid alone is considerably higher at 39%, and minimized to 7% when including ultra-deep Rubin data. For UltraVISTA-like bright galaxies, we find that Euclid (I-Y)>2.8 and (Y-J)<1.4 colour criteria can separate contaminants from true z>6 galaxies, although these are applicable to only 54% of the contaminants, as many have unconstrained (I-Y) colours. In the most optimistic scenario, these cuts reduce the contamination fraction to 1% whilst preserving 81% of the fiducial z>6 sample. For the faint mock sample, colour cuts are infeasible., Comment: 27 pages, 14 figures, 9 tables; version accepted for publication by A&A
Published: 2022
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50. Euclid preparation. XVIII. The NISP photometric system

Author: Euclid Collaboration, Schirmer, M., Jahnke, K., Seidel, G., Aussel, H., Bodendorf, C., Grupp, F., Hormuth, F., Wachter, S., Appleton, P. N., Barbier, R., Brinchmann, J., Carrasco, J. M., Castander, F. J., Coupon, J., De Paolis, F., Franco, A., Ganga, K., Hudelot, P., Jullo, E., Lancon, A., Nucita, A. A., Paltani, S., Smadja, G., Venancio, L. M. G., Strafella, F., Weiler, M., Amara, A., Auphan, T., Auricchio, N., Balestra, A., Bender, R., Bonino, D., Branchini, E., Brescia, M., Capobianco, V., Carbone, C., Carretero, J., Casas, R., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Costille, A., Courbin, F., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hornstrup, A., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lloro, I., Maciaszek, T., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Nichol, R. C., Niemi, S. M., Padilla, C., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Prieto, E., Raison, F., Rhodes, J., Rix, H. -W., Roncarelli, M., Rossetti, E., Saglia, R., Sartoris, B., Scaramella, R., Schneider, P., Secroun, A., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Trifoglio, M., Valentijn, E. A., Valenziano, L., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Boucaud, A., Camera, S., Farinelli, R., Graciá-Carpio, J., Maino, D., Medinaceli, E., Mei, S., Morisset, N., Polenta, G., Renzi, A., Romelli, E., Tenti, M., Vassallo, T., Zacchei, A., Zucca, E., Baccigalupi, C., Balaguera-Antolínez, A., Biviano, A., Blanchard, A., Borgani, S., Bozzo, E., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Colodro-Conde, C., Cooray, A. R., Courtois, H. M., Crocce, M., Cuby, J. -G., Davini, S., de la Torre, S., Di Ferdinando, D., Escartin, J. A., Farina, M., Ferreira, P. G., Finelli, F., Fotopoulou, S., Galeotta, S., Garcia-Bellido, J., Gaztanaga, E., George, K., Gozaliasl, G., Hook, I. M., Ilić, S., Kansal, V., Kashlinsky, A., Keihanen, E., Kirkpatrick, C. C., Lindholm, V., Mainetti, G., Maoli, R., Martinelli, M., Martinet, N., Maturi, M., Mauri, N., McCracken, H. J., Metcalf, R. B., Monaco, P., Morgante, G., Nightingale, J., Patrizii, L., Peel, A., Popa, V., Porciani, C., Potter, D., Reimberg, P., Riccio, G., Sánchez, A. G., Sapone, D., Scottez, V., Sefusatti, E., Teyssier, R., Tutusaus, I., Valieri, C., Valiviita, J., Viel, M., and Hildebrandt, H.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Euclid will be the first space mission to survey most of the extragalactic sky in the 0.95-2.02 $\mu$m range, to a 5$\sigma$ point-source median depth of 24.4 AB mag. This unique photometric data set will find wide use beyond Euclid's core science. In this paper, we present accurate computations of the Euclid Y_E, J_E and H_E passbands used by the Near-Infrared Spectrometer and Photometer (NISP), and the associated photometric system. We pay particular attention to passband variations in the field of view, accounting among others for spatially variable filter transmission, and variations of the angle of incidence on the filter substrate using optical ray tracing. The response curves' cut-on and cut-off wavelengths - and their variation in the field of view - are determined with 0.8 nm accuracy, essential for the photometric redshift accuracy required by Euclid. After computing the photometric zeropoints in the AB mag system, we present linear transformations from and to common ground-based near-infrared photometric systems, for normal stars, red and brown dwarfs, and galaxies separately. A Python tool to compute accurate magnitudes for arbitrary passbands and spectral energy distributions is provided. We discuss various factors from space weathering to material outgassing that may slowly alter Euclid's spectral response. At the absolute flux scale, the Euclid in-flight calibration program connects the NISP photometric system to Hubble Space Telescope spectrophotometric white dwarf standards; at the relative flux scale, the chromatic evolution of the response is tracked at the milli-mag level. In this way, we establish an accurate photometric system that is fully controlled throughout Euclid's lifetime., Comment: 33 pages, 25 figures, accepted for publication in A&A
Published: 2022
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