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51. Euclid: Identification of asteroid streaks in simulated images using deep learning

Author: Pöntinen, M., Granvik, M., Nucita, A. A., Conversi, L., Altieri, B., Carry, B., O'Riordan, C. M., Scott, D., Aghanim, N., Amara, A., Amendola, L., Auricchio, N., Baldi, M., Bonino, D., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., 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., Grazian, A., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., 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., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., 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., 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., Kleijn, G. Verdoes, Wang, Y., Weller, J., Zamorani, G., Zoubian, J., and Scottez, V.
Subjects: Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Machine Learning
Abstract: Up to 150000 asteroids will be visible in the images of the ESA Euclid space telescope, and the instruments of Euclid offer multiband visual to near-infrared photometry and slitless spectra of these objects. Most asteroids will appear as streaks in the images. Due to the large number of images and asteroids, automated detection methods are needed. A non-machine-learning approach based on the StreakDet software was previously tested, but the results were not optimal for short and/or faint streaks. We set out to improve the capability to detect asteroid streaks in Euclid images by using deep learning. We built, trained, and tested a three-step machine-learning pipeline with simulated Euclid images. First, a convolutional neural network (CNN) detected streaks and their coordinates in full images, aiming to maximize the completeness (recall) of detections. Then, a recurrent neural network (RNN) merged snippets of long streaks detected in several parts by the CNN. Lastly, gradient-boosted trees (XGBoost) linked detected streaks between different Euclid exposures to reduce the number of false positives and improve the purity (precision) of the sample. The deep-learning pipeline surpasses the completeness and reaches a similar level of purity of a non-machine-learning pipeline based on the StreakDet software. Additionally, the deep-learning pipeline can detect asteroids 0.25-0.5 magnitudes fainter than StreakDet. The deep-learning pipeline could result in a 50% increase in the number of detected asteroids compared to the StreakDet software. There is still scope for further refinement, particularly in improving the accuracy of streak coordinates and enhancing the completeness of the final stage of the pipeline, which involves linking detections across multiple exposures., Comment: 18 pages, 11 figures
Published: 2023

52. Euclid: The search for primordial features

Author: Ballardini, M., Akrami, Y., Finelli, F., Karagiannis, D., Li, B., Li, Y., Sakr, Z., Sapone, D., Achúcarro, A., Baldi, M., Bartolo, N., Cañas-Herrera, G., Casas, S., Murgia, R., Winther, H. A., Viel, M., Andrews, A., Jasche, J., Lavaux, G., Hazra, D. K., Paoletti, D., Valiviita, J., Amara, A., Andreon, S., Auricchio, N., Battaglia, P., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Dubath, F., Dupac, X., Farina, M., Farrens, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Kermiche, S., Kiessling, A., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Martinet, N., Marulli, F., Massey, R., 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., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sartoris, B., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., 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., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., and Scottez, V.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Primordial features, in particular oscillatory signals, imprinted in the primordial power spectrum of density perturbations represent a clear window of opportunity for detecting new physics at high-energy scales. Future spectroscopic and photometric measurements from the $Euclid$ space mission will provide unique constraints on the primordial power spectrum, thanks to the redshift coverage and high-accuracy measurement of nonlinear scales, thus allowing us to investigate deviations from the standard power-law primordial power spectrum. We consider two models with primordial undamped oscillations superimposed on the matter power spectrum, one linearly spaced in $k$-space the other logarithmically spaced in $k$-space. We forecast uncertainties applying a Fisher matrix method to spectroscopic galaxy clustering, weak lensing, photometric galaxy clustering, cross correlation between photometric probes, spectroscopic galaxy clustering bispectrum, CMB temperature and $E$-mode polarization, temperature-polarization cross correlation, and CMB weak lensing. We also study a nonlinear density reconstruction method to retrieve the oscillatory signals in the primordial power spectrum. We find the following percentage relative errors in the feature amplitude with $Euclid$ primary probes for the linear (logarithmic) feature model: 21% (22%) in the pessimistic settings and 18% (18%) in the optimistic settings at 68.3% confidence level (CL) using GC$_{\rm sp}$+WL+GC$_{\rm ph}$+XC. Combining all the sources of information explored expected from $Euclid$ in combination with future SO-like CMB experiment, we forecast ${\cal A}_{\rm lin} \simeq 0.010 \pm 0.001$ at 68.3% CL and ${\cal A}_{\rm log} \simeq 0.010 \pm 0.001$ for GC$_{\rm sp}$(PS rec + BS)+WL+GC$_{\rm ph}$+XC+SO-like both for the optimistic and pessimistic settings over the frequency range $(1,\,10^{2.1})$., Comment: 23 pages, 9 figures, 4 tables
Published: 2023
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53. Prospects for $\gamma$-ray observations of the Perseus galaxy cluster with the Cherenkov Telescope Array

Author: Consortium, The Cherenkov Telescope Array, Abe, K., Abe, S., Acero, F., Acharyya, A., Adam, R., Aguasca-Cabot, A., Agudo, I., Aguirre-Santaella, A., Alfaro, J., Alfaro, R., Alvarez-Crespo, N., Batista, R. Alves, Amans, J. -P., Amato, E., Angüner, E. O., Antonelli, L. A., Aramo, C., Araya, M., Arcaro, C., Arrabito, L., Asano, K., Ascasíbar, Y., Aschersleben, J., Ashkar, H., Stuani, L. Augusto, Baack, D., Backes, M., Baktash, A., Balazs, C., Balbo, M., Ballester, O., Larriva, A. Baquero, Martins, V. Barbosa, de Almeida, U. Barres, Barrio, J. A., Batista, P. I., Batkovic, I., Batzofin, R., Baxter, J., González, J. Becerra, Beck, G., Tjus, J. Becker, Benbow, W., Medrano, J. Bernete, Bernlöhr, K., Berti, A., Bertucci, B., Beshley, V., Bhattacharjee, P., Bhattacharyya, S., Bi, B., Biederbeck, N., Biland, A., Bissaldi, E., Biteau, J., Blanch, O., Blazek, J., Boisson, C., Bolmont, J., Bordas, P., Bosnjak, Z., Bottacini, E., Bradascio, F., Braiding, C., Bronzini, E., Brose, R., Brown, A. M., Brun, F., Brunetti, G., Bucciantini, N., Bulgarelli, A., Burelli, I., Burmistrov, L., Burton, M., Bylund, T., Calisse, P. G., Campoy-Ordaz, A., Cantlay, B. K., Capalbi, M., Caproni, A., Capuzzo-Dolcetta, R., Caraveo, P., Caroff, S., Carosi, R., Carquin, E., Carrasco, M. -S., Cascone, E., Cassol, F., Castro-Tirado, A. J., Cerasole, D., Cerruti, M., Chadwick, P., Chaty, S., Chen, A. W., Chernyakova, M., Chiavassa, A., Chudoba, J., Chytka, L., Cifuentes, A., Araujo, C. H. Coimbra, Conforti, V., Conte, F., Contreras, J. L., Cortina, J., Costa, A., Costantini, H., Cotter, G., Cristofari, P., Cuevas, O., Curtis-Ginsberg, Z., D'Amico, G., D'Ammando, F., Dalchenko, M., Dazzi, F., de Lavergne, M. de Bony, De Caprio, V., Laadim, F. De Frondat, Pino, E. M. de Gouveia Dal, De Lotto, B., De Lucia, M., De Martino, D., de Menezes, R., de Naurois, M., De Simone, N., de Souza, V., del Valle, M. V., Delagnes, E., Giler, A. G. Delgado, Delgado, C., Dell'aiera, M., della Volpe, D., Depaoli, D., Di Girolamo, T., Di Piano, A., Di Pierro, F., Di Tria, R., Di Venere, L., Diebold, S., Djannati-Ataï, A., Djuvsland, J., Dominik, R. M., Donini, A., Dorner, D., Dörner, J., Doro, M., Anjos, R. D. C. dos, Dournaux, J. -L., Duangchan, C., Dubos, C., Dumora, D., Dwarkadas, V. V., Ebr, J., Eckner, C., Egberts, K., Einecke, S., Elsässer, D., Emery, G., Godoy, M. Escobar, Escudero, J., Esposito, P., Ettori, S., Evoli, C., Falceta-Goncalves, D., Ramazani, V. Fallah, Fattorini, A., Faure, A., Fedorova, E., Fegan, S., Feijen, K., Feng, Q., Ferrand, G., Ferrarotto, F., Fiandrini, E., Fiasson, A., Filipovic, M., Fioretti, V., Foffano, L., Guiteras, L. Font, Fontaine, G., Fröse, S., Fukazawa, Y., Fukui, Y., Gaggero, D., Galanti, G., Gallozzi, S., Gammaldi, V., Garczarczyk, M., Gasbarra, C., Gasparrini, D., Gaug, M., Ghalumyan, A., Gianotti, F., Giarrusso, M., Giesbrecht, J., Giglietto, N., Giordano, F., Glicenstein, J. -F., Göksu, H., Goldoni, P., González, J. M., González, M. M., Coelho, J. Goulart, Granot, J., Grau, R., Gréaux, L., Green, D., Green, J. G., Grenier, I., Grolleron, G., Grube, J., Gueta, O., Hackfeld, J., Hadasch, D., Hamal, P., Hanlon, W., Hara, S., Harvey, V. M., Hassan, T., Heckmann, L., Heller, M., Cadena, S. Hernández, Hervet, O., Hie, J., Hiroshima, N., Hnatyk, B., Hnatyk, R., Hoang, J., Hoffmann, D., Hofmann, W., Holder, J., Horan, D., Horvath, P., Hrupec122, D., Hütten, M., Iarlori, M., Inada, T., Incardona, F., Inoue, S., Iocco, F., Iori, M., Jamrozy, M., Janecek, P., Jankowsky, F., Jarnot, C., Jean, P., Martínez, I. Jiménez, Jin, W., Juramy-Gilles, C., Jurysek, J., Kagaya, M., Kantzas, D., Karas, V., Katagiri, H., Kataoka, J., Kaufmann, S., Kerszberg, D., Khélifi, B., Kissmann, R., Kleiner, T., Kluge, G., Kluźniak, W., Knödlseder, J., Kobayashi, Y., Kohri, K., Komin, N., Kornecki, P., Kosack, K., Kowal, G., Kubo, H., Kushida, J., La Barbera, A., La Palombara, N., Láinez, M., Lamastra, A., Lapington, J., Laporte, P., Lazarević, S., Leitgeb, F., Lemoine-Goumard, M., Lenain, J. -P., Leone, F., Leto, G., Leuschner, F., Lindfors, E., Linhoff, M., Liodakis, I., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Luque-Escamilla, P. L., Macias, O., Mackey, J., Majumdar, P., Malyshev, D., Mandat, D., Manganaro, M., Manicò, G., Mariotti, M., Markoff, S., Márquez, I., Marquez, P., Marsella, G., Martínez, G. A., Martínez, M., Martinez, O., Marty, C., Mas-Aguilar, A., Mastropietro, M., Maurin, G., Mazin, D., Melkumyan, D., Mello, A. J. T. S., Meunier, J. -L., Meyer, D. M. -A., Meyer, M., Miceli, D., Michailidis, M., Michałowski, J., Miener, T., Miranda, J. M., Mitchell, A., Mizote, M., Mizuno, T., Moderski, R., Molero, M., Molfese, C., Molina, E., Montaruli, T., Morcuende, D., Morik, K., Morlino, G., Morselli, A., Moulin, E., Zamanillo, V. Moya, Munari, K., Murach, T., Muraczewski, A., Muraishi, H., Nagataki, S., Nakamori, T., Nemmen, R., Neyroud, N., Nickel, L., Niemiec, J., Nieto, D., Rosillo, M. Nievas, Nikołajuk, M., Nishijima, K., Noda, K., Nosek, D., Novotny, V., Nozaki, S., O'Brien, P., Ohishi, M., Ohtani, Y., Okumura, A., Olive, J. -F., Olmi, B., Ong, R. A., Orienti, M., Orito, R., Orlandini, M., Orlando, E., Ostrowski, M., Oya, I., Pagliaro, A., Palatiello, M., Panebianco, G., Paneque, D., Pantaleo, F. R., Paoletti, R., Paredes, J. M., Parmiggiani, N., Patel, S. R., Patricelli, B., Pavlović, D., Pech, M., Pecimotika, M., Pensec, U., Peresano, M., Pérez-Romero, J., Peron, G., Persic, M., Petrucci, P. -O., Petruk, O., Piano, G., Pierre, E., Pietropaolo, E., Pintore, F., Pirola, G., Pita, S., Plard, C., Podobnik, F., Pohl, M., Polo, M., Pons, E., Ponti, G., Prandini, E., Prast, J., Principe, G., Priyadarshi, C., Produit, N., Pueschel, E., Pühlhofer, G., Pumo, M. L., Punch, M., Queiroz, F., Quirrenbach, A., Rainò, S., Rando, R., Razzaque, S., Recchia, S., Regeard, M., Reichherzer, P., Reimer, A., Reimer, O., Reisenegger, A., Rhode, W., Ribeiro, D., Ribó, M., Richtler, T., Rico, J., Rieger, F., Righi, C., Riitano, L., Rizi, V., Roache, E., Fernandez, G. Rodriguez, Rodríguez-Vázquez, J. J., Romano, P., Romeo, G., Rosado, J., de Leon, A. Rosales, Rowell, G., Rudak, B., Rulten, C. B., Russo, F., Sadeh, I., Saha, L., Saito, T., Salzmann, H., Sanchez, D., Sánchez-Conde, M., Sangiorgi, P., Sano, H., Santander, M., Santangelo, A., Santos-Lima, R., Sanuy, A., Šarić, T., Sarkar, A., Sarkar, S., Satalecka, K., Saturni, F. G., Savchenko, V., Scherer, A., Schipani, P., Schleicher, B., Schubert, J. L., Schussler, F., Schwanke, U., Schwefer, G., Arroyo, M. Seglar, Seiji, S., Semikoz, D., Sergijenko, O., Servillat, M., Sguera, V., Shang, R. Y., Sharma, P., Siejkowski, H., Sinha, A., Siqueira, C., Sliusar, V., Slowikowska, A., Sol, H., Specovius, A., Spencer, S. T., Spiga, D., Stamerra, A., Stanič, S., Starecki, T., Starling, R., Stawarz, Ł., Steppa, C., Stolarczyk, T., Strišković, J., Suda, Y., Suomijärvi, T., Tajima, H., Tak, D., Takahashi, M., Takeishi, R., Tanaka, S. J., Tavernier, T., Tejedor, L. A., Terauchi, K., Terrier, R., Teshima, M., Tian, W. W., Tibaldo, L., Tibolla, O., Torradeflot, F., Torres, D. F., Torresi, E., Tosti, G., Tosti, L., Tothill, N., Toussenel, F., Touzard, V., Tramacere, A., Travnicek, P., Tripodo, G., Truzzi, S., Tsiahina, A., Tutone, A., Vacula, M., Vallage, B., Vallania, P., van Eldik, C., van Scherpenberg, J., Vandenbroucke, J., Vassiliev, V., Acosta, M. Vázquez, Vecchi, M., Ventura, S., Vercellone, S., Verna, G., Viana, A., Viaux, N., Vigliano, A., Vigorito, C. F., Vitale, V., Vodeb, V., Voisin, V., Vorobiov, S., Voutsinas, G., Vovk, I., Vuillaume, T., Wagner, S. J., Walter, R., Wechakama, M., White, R., Wierzcholska, A., Will, M., Williams, D. A., Wohlleben, F., Wolter, A., Yamamoto, T., Yamazaki, R., Yoshida, T., Yoshikoshi, T., Zacharias, M., Zaharijas, G., Zavrtanik, D., Zavrtanik, M., Zdziarski, A. A., Zech, A., Zhdanov, V. I., Živec, M., Zuriaga-Puig, J., and Luque, P. De la Torre
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology
Abstract: Galaxy clusters are expected to be dark matter (DM) reservoirs and storage rooms for the cosmic-ray protons (CRp) that accumulate along the cluster's formation history. Accordingly, they are excellent targets to search for signals of DM annihilation and decay at gamma-ray energies and are predicted to be sources of large-scale gamma-ray emission due to hadronic interactions in the intracluster medium. We estimate the sensitivity of the Cherenkov Telescope Array (CTA) to detect diffuse gamma-ray emission from the Perseus galaxy cluster. We perform a detailed spatial and spectral modelling of the expected signal for the DM and the CRp components. For each, we compute the expected CTA sensitivity. The observing strategy of Perseus is also discussed. In the absence of a diffuse signal (non-detection), CTA should constrain the CRp to thermal energy ratio within the radius $R_{500}$ down to about $X_{500}<3\times 10^{-3}$, for a spatial CRp distribution that follows the thermal gas and a CRp spectral index $\alpha_{\rm CRp}=2.3$. Under the optimistic assumption of a pure hadronic origin of the Perseus radio mini-halo and depending on the assumed magnetic field profile, CTA should measure $\alpha_{\rm CRp}$ down to about $\Delta\alpha_{\rm CRp}\simeq 0.1$ and the CRp spatial distribution with 10% precision. Regarding DM, CTA should improve the current ground-based gamma-ray DM limits from clusters observations on the velocity-averaged annihilation cross-section by a factor of up to $\sim 5$, depending on the modelling of DM halo substructure. In the case of decay of DM particles, CTA will explore a new region of the parameter space, reaching models with $\tau_{\chi}>10^{27}$s for DM masses above 1 TeV. These constraints will provide unprecedented sensitivity to the physics of both CRp acceleration and transport at cluster scale and to TeV DM particle models, especially in the decay scenario., Comment: 93 pages (including author list, appendix and references), 143 figures. Submitted to JCAP
Published: 2023
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54. 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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55. 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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56. Euclid: Constraining linearly scale-independent modifications of gravity with the spectroscopic and photometric primary probes

Author: Frusciante, N., Pace, F., Cardone, V. F., Casas, S., Tutusaus, I., Ballardini, M., Bellini, E., Benevento, G., Bose, B., Valageas, P., Bartolo, N., Brax, P., Ferreira, P. G., Finelli, F., Koyama, K., Legrand, L., Lombriser, L., Paoletti, D., Pietroni, M., Rozas-Fernández, A., Sakr, Z., Silvestri, A., Vernizzi, F., Winther, H. A., Aghanim, N., Amendola, L., Auricchio, N., Azzollini, R., Baldi, M., 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., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. 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., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Nightingale, J., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Saglia, R., Sapone, D., Sartoris, B., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. A. Verdoes, Wang, Y., Zacchei, A., Zamorani, G., Zoubian, J., and Scottez, V.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract: The future Euclid space satellite mission will offer an invaluable opportunity to constrain modifications to Einstein's general relativity at cosmic scales. We focus on modified gravity models characterised, at linear scales, by a scale-independent growth of perturbations while featuring different testable types of derivative screening mechanisms at smaller non-linear scales. We considered three specific models, namely JBD, a scalar-tensor theory with a flat potential, the nDGP gravity, a braneworld model in which our Universe is a four-dimensional brane embedded in a five-dimensional Minkowski space-time, and $k$-mouflage (KM) gravity, an extension of $k$-essence scenarios with a universal coupling of the scalar field to matter. In preparation for real data, we provide forecasts from spectroscopic and photometric primary probes by Euclid on the cosmological parameters and the additional parameters of the models, respectively, $\omega_{\rm BD}$, $\Omega_{\rm rc}$ and $\epsilon_{2,0}$. The forecast analysis employs the Fisher matrix method applied to weak lensing (WL); photometric galaxy clustering (GCph), spectroscopic galaxy clustering (GCsp) and the cross-correlation (XC) between GCph and WL. In an optimistic setting at 68.3\% confidence interval, we find the following percentage relative errors with Euclid alone: for $\log_{10}{\omega_{\rm BD}}$, with a fiducial value of $\omega_{\rm BD}=800$, 27.1\% using GCsp alone, 3.6\% using GCph+WL+XC and 3.2\% using GCph+WL+XC+GCsp; for $\log_{10}{\Omega_{\rm rc}}$, with a fiducial value of $\Omega_{\rm rc}=0.25$, we find 93.4\%, 20\% and 15\% respectively; and finally, for $\epsilon_{2,0}=-0.04$, we find 3.4\%, 0.15\%, and 0.14\%. (abridged), Comment: 23 pages, 8 figures, 4 tables, 1 appendix, matches Journal version
Published: 2023
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57. Euclid: Constraints on f(R) cosmologies from the spectroscopic and photometric primary probes

Author: Casas, S., Cardone, V. F., Sapone, D., Frusciante, N., Pace, F., Parimbelli, G., Archidiacono, M., Koyama, K., Tutusaus, I., Camera, S., Martinelli, M., Pettorino, V., Sakr, Z., Lombriser, L., Silvestri, A., Pietroni, M., Vernizzi, F., Kunz, M., Kitching, T., Pourtsidou, A., Lacasa, F., Carbone, C., Garcia-Bellido, J., Aghanim, N., Altieri, B., Amara, A., Auricchio, N., Baldi, M., Bodendorf, C., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Carretero, 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., DaSilva, A., Degaudenzi, H., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., 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., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Marulli, F., Massey, R., Medinaceli, E., 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., 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., Sartoris, B., Scottez, V., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., and Zoubian, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract: $\textit{Euclid}$ will provide a powerful compilation of data including spectroscopic redshifts, the angular clustering of galaxies, weak lensing cosmic shear, and the cross-correlation of these last two photometric observables. In this study we extend recently presented $\textit{Euclid}$ forecasts into the Hu-Sawicki $f(R)$ cosmological model, a popular extension of the Hilbert-Einstein action that introduces an universal modified gravity force in a scale-dependent way. Our aim is to estimate how well future $\textit{Euclid}$ data will be able to constrain the extra parameter of the theory, $f_{R0}$, for the range in which this parameter is still allowed by current observations. For the spectroscopic probe, we use a phenomenological approach for the scale dependence of the growth of perturbations in the terms related to baryon acoustic oscillations and redshift-space distortions. For the photometric observables, we use a fitting formula that captures the modifications in the non-linear matter power spectrum caused by the $f(R)$ model. We show that, in an optimistic setting, and for a fiducial value of $f_{R0} = 5 \times 10^{-6}$, $\textit{Euclid}$ alone will be able to constrain the additional parameter $\log f_{R0}$ at the $3\%$ level, using spectroscopic galaxy clustering alone; at the $1.4\%$ level, using the combination of photometric probes on their own; and at the $1\%$ level, using the combination of spectroscopic and photometric observations. This last constraint corresponds to an error of the order of $6 \times 10^{-7}$ at the $1\sigma$ level on the model parameter $f_{R0} = 5 \times 10^{-6}$. We report also forecasted constraints for $f_{R0} = 5 \times 10^{-5}$ and $f_{R0} = 5 \times 10^{-7}$ and show that in the optimistic scenario, $\textit{Euclid}$ will be able to distinguish these models from $\Lambda\mathrm{CDM}$ at more than 3$\sigma$. (abridged), Comment: 10 Figures, 3 Tables, 1 Appendix
Published: 2023

58. 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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59. Euclid: Validation of the MontePython forecasting tools

Author: Casas, S., Lesgourgues, J., Schöneberg, N., M., Sabarish V., Rathmann, L., Doerenkamp, M., Archidiacono, M., Bellini, E., Clesse, S., Frusciante, N., Martinelli, M., Pace, F., Sapone, D., Sakr, Z., Blanchard, A., Brinckmann, T., Camera, S., Carbone, C., Ilić, S., Markovic, K., Pettorino, V., Tutusaus, I., Aghanim, N., Amara, A., Amendola, L., Auricchio, N., Baldi, M., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Cardone, V. F., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Degaudenzi, H., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Farrens, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hormuth, F., Hornstrup, A., Jahnke, K., Kümmel, M., Kiessling, A., Kilbinger, M., Kitching, T., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Marulli, F., Massey, R., Medinaceli, E., Mei, S., 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., 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., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Scottez, V., and Veropalumbo, A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Euclid mission of the European Space Agency will perform a survey of weak lensing cosmic shear and galaxy clustering in order to constrain cosmological models and fundamental physics. We expand and adjust the mock Euclid likelihoods of the MontePython software in order to match the exact recipes used in previous Euclid Fisher matrix forecasts for several probes: weak lensing cosmic shear, photometric galaxy clustering, the cross-correlation between the latter observables, and spectroscopic galaxy clustering. We also establish which precision settings are required when running the Einstein-Boltzmann solvers CLASS and CAMB in the context of Euclid. For the minimal cosmological model, extended to include dynamical dark energy, we perform Fisher matrix forecasts based directly on a numerical evaluation of second derivatives of the likelihood with respect to model parameters. We compare our results with those of other forecasting methods and tools. We show that such MontePython forecasts agree very well with previous Fisher forecasts published by the Euclid Collaboration, and also, with new forecasts produced by the CosmicFish code, now interfaced directly with the two Einstein-Boltzmann solvers CAMB and CLASS. Moreover, to establish the validity of the Gaussian approximation, we show that the Fisher matrix marginal error contours coincide with the credible regions obtained when running Monte Carlo Markov Chains with MontePython while using the exact same mock likelihoods. The new Euclid forecast pipelines presented here are ready for use with additional cosmological parameters, in order to explore extended cosmological models., Comment: 45 pages, 24 figures
Published: 2023

60. 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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61. Euclid: Cosmology forecasts from the void-galaxy cross-correlation function with reconstruction

Author: Radinović, S., Nadathur, S., Winther, H. -A., Percival, W. J., Woodfinden, A., Massara, E., Paillas, E., Contarini, S., Hamaus, N., Kovacs, A., Pisani, A., Verza, G., Aubert, M., Amara, A., Auricchio, N., Baldi, M., Bonino, D., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Da Silva, A., Douspis, M., Dubath, F., Dupac, X., 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., Haugan, S. V. H., Holmes, W., Hornstrup, A., Jahnke, K., Kümmel, M., Kiessling, A., Kilbinger, M., Kitching, T., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., 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., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rosset, C., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., 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., Weller, J., Zamorani, G., Zoubian, J., and Scottez, V.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We investigate the cosmological constraints that can be expected from measurement of the cross-correlation of galaxies with cosmic voids identified in the Euclid spectroscopic survey, which will include spectroscopic information for tens of millions of galaxies over $15\,000$ deg$^2$ of the sky in the redshift range $0.9\leq z<1.8$. We do this using simulated measurements obtained from the Flagship mock catalogue, the official Euclid mock that closely matches the expected properties of the spectroscopic data set. To mitigate anisotropic selection-bias effects, we use a velocity field reconstruction method to remove large-scale redshift-space distortions from the galaxy field before void-finding. This allows us to accurately model contributions to the observed anisotropy of the cross-correlation function arising from galaxy velocities around voids as well as from the Alcock-Paczynski effect, and we study the dependence of constraints on the efficiency of reconstruction. We find that Euclid voids will be able to constrain the ratio of the transverse comoving distance $D_{\rm M}$ and Hubble distance $D_{\rm H}$ to a relative precision of about $0.3\%$, and the growth rate $f\sigma_8$ to a precision of between $5\%$ and $8\%$ in each of four redshift bins covering the full redshift range. In the standard cosmological model, this translates to a statistical uncertainty $\Delta\Omega_\mathrm{m}=\pm0.0028$ on the matter density parameter from voids, better than can be achieved from either Euclid galaxy clustering and weak lensing individually. We also find that voids alone can measure the dark energy equation of state to $6\%$ precision., Comment: 20 pages, 13 figures, accepted version
Published: 2023
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62. 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

63. Euclid preparation. XXXII. Evaluating the weak lensing cluster mass biases using the Three Hundred Project hydrodynamical simulations

Author: Euclid Collaboration, Giocoli, C., Meneghetti, M., Rasia, E., Borgani, S., Despali, G., Lesci, G. F., Marulli, F., Moscardini, L., Sereno, M., Cui, W., Knebe, A., Yepes, G., Castro, T., Corasaniti, P. -S., Pires, S., Castignani, G., Ingoglia, L., Schrabback, T., Pratt, G. W., Brun, A. M. C. Le, Aghanim, N., Amendola, L., Auricchio, N., Baldi, M., 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., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hornstrup, A., Jahnke, K., Kümmel, M., Kermiche, S., Kilbinger, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Massey, R., Maurogordato, S., Mei, S., Merlin, E., Meylan, G., Moresco, M., Munari, E., Niemi, S. -M., Nightingale, J., Nutma, T., 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., Schneider, P., Secroun, A., 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., 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., Israel, H., Keihänen, E., Lindholm, V., Mauri, N., Neissner, C., Schirmer, M., Scottez, V., Tenti, M., Zucca, E., Akrami, Y., Baccigalupi, C., Ballardini, M., Bernardeau, F., Biviano, A., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Chambers, K. C., Cooray, A. R., 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., Gabarra, L., Ganga, K., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Hook, I., MU\{N}OZ, A. JIMENEZ, Joachimi, B., 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., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Peel, A., Pollack, J., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Schneider, A., Sefusatti, E., Shulevski, A., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Valiviita, J., Veropalumbo, A., Viel, M., and Zinchenko, I. A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The photometric catalogue of galaxy clusters extracted from ESA Euclid data is expected to be very competitive for cosmological studies. Using state-of-the-art hydrodynamical simulations, we present systematic analyses simulating the expected weak lensing profiles from clusters in a variety of dynamic states and at wide range of redshifts. In order to derive cluster masses, we use a model consistent with the implementation within the Euclid Consortium of the dedicated processing function and find that, when jointly modelling mass and the concentration parameter of the Navarro-Frenk-White halo profile, the weak lensing masses tend to be, on average, biased low by 5-10% with respect to the true mass, up to z=0.5. Using a fixed value for the concentration $c_{200} = 3$, the mass bias is diminished below 5%, up to z=0.7, along with its relative uncertainty. Simulating the weak lensing signal by projecting along the directions of the axes of the moment of inertia tensor ellipsoid, we find that orientation matters: when clusters are oriented along the major axis, the lensing signal is boosted, and the recovered weak lensing mass is correspondingly overestimated. Typically, the weak lensing mass bias of individual clusters is modulated by the weak lensing signal-to-noise ratio, related to the redshift evolution of the number of galaxies used for weak lensing measurements: the negative mass bias tends to be larger toward higher redshifts. However, when we use a fixed value of the concentration parameter, the redshift evolution trend is reduced. These results provide a solid basis for the weak-lensing mass calibration required by the cosmological application of future cluster surveys from Euclid and Rubin., Comment: Accepted for publication in Astronomy & Astrophysics
Published: 2023
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64. 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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65. Euclid preparation. XXVII. Covariance model validation for the 2-point correlation function of galaxy clusters

Author: Euclid Collaboration, Fumagalli, A., Saro, A., Borgani, S., Castro, T., Costanzi, M., Monaco, P., Munari, E., Sefusatti, E., Aghanim, N., Auricchio, N., Baldi, M., 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., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Dubath, F., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hornstrup, A., Hudelot, P., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., 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., Raison, F., Rebolo-Lopez, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., 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., 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., Lindholm, V., Maino, D., Mauri, N., Neissner, C., Scottez, V., Zucca, E., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Bernardeau, F., Biviano, A., Blanchard, A., Borlaff, A. S, Burigana, C., Cabanac, R., Carvalho, C. S., Casas, S., Castignani, G., Chambers, K., Cooray, A. R., Coupon, J., Courtois, H. M., Davini, S., de la Torre, S., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Ferreira, P. G., Finelli, F., Garcia-Bellido, J., George, K., Gozaliasl, G., Hildebrandt, H., Hook, I., Muňoz, A. Jimenez, Joachimi, B., Kansal, V., Keihänen, E., Kirkpatrick, C. C., Loureiro, A., Magliocchetti, M., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Pollack, J. E., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Pöntinen, M., Sánchez, A. G., Sakr, Z., Schirmer, M., Sereno, M., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Valieri, C., Valiviita, J., Veropalumbo, A., and Viel, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, 85A40
Abstract: Aims. We validate a semi-analytical model for the covariance of real-space 2-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrate a simple model to accurately describe the clustering covariance. Then, we use such a model to quantify the likelihood analysis response to variations of the covariance, and investigate the impact of a cosmology-dependent matrix at the level of statistics expected for the Euclid survey of galaxy clusters. Results. We find that a Gaussian model with Poissonian shot-noise does not correctly predict the covariance of the 2-point correlation function of galaxy clusters. By introducing few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with 10 per cent accuracy, with differences of about 5 per cent on the figure of merit of the cosmological parameters $\Omega_{\rm m}$ and $\sigma_8$. Also, we find that the cosmology-dependence of the covariance adds valuable information that is not contained in the mean value, significantly improving the constraining power of cluster clustering. Finally, we find that the cosmological figure of merit can be further improved by taking mass binning into account. Our results have significant implications for the derivation of cosmological constraints from the 2-point clustering statistics of the Euclid survey of galaxy clusters., Comment: 18 pages, 14 figures
Published: 2022

66. Euclid: Modelling massive neutrinos in cosmology -- a code comparison

Author: Adamek, J., Angulo, R. E., Arnold, C., Baldi, M., Biagetti, M., Bose, B., Carbone, C., Castro, T., Dakin, J., Dolag, K., Elbers, W., Fidler, C., Giocoli, C., Hannestad, S., Hassani, F., Hernández-Aguayo, C., Koyama, K., Li, B., Mauland, R., Monaco, P., Moretti, C., Mota, D. F., Partmann, C., Parimbelli, G., Potter, D., Schneider, A., Schulz, S., Smith, R. E., Springel, V., Stadel, J., Tram, T., Viel, M., Villaescusa-Navarro, F., Winther, H. A., Wright, B. S., Zennaro, M., Aghanim, N., Amendola, L., Auricchio, N., Bonino, D., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Cardone, V. F., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Grazian, A., Haugan, S. V., Holmes, W., Hornstrup, A., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., 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., 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., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Fabbian, G., and Scottez, V.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The measurement of the absolute neutrino mass scale from cosmological large-scale clustering data is one of the key science goals of the Euclid mission. Such a measurement relies on precise modelling of the impact of neutrinos on structure formation, which can be studied with $N$-body simulations. Here we present the results from a major code comparison effort to establish the maturity and reliability of numerical methods for treating massive neutrinos. The comparison includes eleven full $N$-body implementations (not all of them independent), two $N$-body schemes with approximate time integration, and four additional codes that directly predict or emulate the matter power spectrum. Using a common set of initial data we quantify the relative agreement on the nonlinear power spectrum of cold dark matter and baryons and, for the $N$-body codes, also the relative agreement on the bispectrum, halo mass function, and halo bias. We find that the different numerical implementations produce fully consistent results. We can therefore be confident that we can model the impact of massive neutrinos at the sub-percent level in the most common summary statistics. We also provide a code validation pipeline for future reference., Comment: 44 pages, 17 figures, 2 tables; v2: minor revision, accepted manuscript; published on behalf of the Euclid Consortium; data available at https://doi.org/10.5281/zenodo.7868793
Published: 2022
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67. 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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68. The PAU Survey & Euclid: Improving broad-band photometric redshifts with multi-task learning

Author: Cabayol, L., Eriksen, M., Carretero, J., Casas, R., Castander, F. J., Fernández, E., Garcia-Bellido, J., Gaztanaga, E., Hildebrandt, H., Hoekstra, H., Joachimi, B., Miquel, R., Padilla, C., Pocino, A., Sanchez, E., Serrano, S., Sevilla, I., Siudek, M., Tallada-Crespí, P., Aghanim, N., Amara, A., Auricchio, N., Baldi, M., Bender, R., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., 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., Fosalba, P., Frailis, M., Franceschi, E., Franzetti, P., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Kümme, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kohley, R., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. M., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Rhodes, J., Riccio, G., Rosset, C., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seide, G., Sirignano, C., Sirri, G., Stanco, L., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E., Valenziano, L., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Mei, S., Scottez, V., and Tramacere, A.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: Current and future imaging surveys require photometric redshifts (photo-zs) to be estimated for millions of galaxies. Improving the photo-z quality is a major challenge but is needed to advance our understanding of cosmology. In this paper we explore how the synergies between narrow-band photometric data and large imaging surveys can be exploited to improve broadband photometric redshifts. We used a multi-task learning (MTL) network to improve broadband photo-z estimates by simultaneously predicting the broadband photo-z and the narrow-band photometry from the broadband photometry. The narrow-band photometry is only required in the training field, which also enables better photo-z predictions for the galaxies without narrow-band photometry in the wide field. This technique was tested with data from the Physics of the Accelerating Universe Survey (PAUS) in the COSMOS field. We find that the method predicts photo-zs that are 13% more precise down to magnitude i_{AB} < 23; the outlier rate is also 40% lower when compared to the baseline network. Furthermore, MTL reduces the photo-z bias for high-redshift galaxies, improving the redshift distributions for tomographic bins with z>1. Applying this technique to deeper samples is crucial for future surveys such as \Euclid or LSST. For simulated data, training on a sample with i_{AB} <23, the method reduces the photo-z scatter by 16% for all galaxies with i_{AB}<25. We also studied the effects of extending the training sample with photometric galaxies using PAUS high-precision photo-zs, which reduces the photo-z scatter by 20% in the COSMOS field., Comment: 20 pages, 16 figures
Published: 2022
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69. Euclid: Calibrating photometric redshifts with spectroscopic cross-correlations

Author: Naidoo, K., Johnston, H., Joachimi, B., Busch, J. L. van den, Hildebrandt, H., Ilbert, O., Lahav, O., Aghanim, N., Altieri, B., Amara, A., Baldi, M., Bender, R., Bodendorf, C., 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., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., 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., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., 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., 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., 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., Weller, J., Wetzstein, M., Zacchei, A., Zamorani, G., Zoubian, J., Andreon, S., Maino, D., Scottez, V., and Wright, A. H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Cosmological constraints from key probes of the Euclid imaging survey rely critically on the accurate determination of the true redshift distributions, $n(z)$, of tomographic redshift bins. We determine whether the mean redshift, $$, of ten Euclid tomographic redshift bins can be calibrated to the Euclid target uncertainties of $\sigma()<0.002\,(1+z)$ via cross-correlation, with spectroscopic samples akin to those from the Baryon Oscillation Spectroscopic Survey (BOSS), Dark Energy Spectroscopic Instrument (DESI), and Euclid's NISP spectroscopic survey. We construct mock Euclid and spectroscopic galaxy samples from the Flagship simulation and measure small-scale clustering redshifts up to redshift $z<1.8$ with an algorithm that performs well on current galaxy survey data. The clustering measurements are then fitted to two $n(z)$ models: one is the true $n(z)$ with a free mean; the other a Gaussian Process modified to be restricted to non-negative values. We show that $$ is measured in each tomographic redshift bin to an accuracy of order 0.01 or better. By measuring the clustering redshifts on subsets of the full Flagship area, we construct scaling relations that allow us to extrapolate the method performance to larger sky areas than are currently available in the mock. For the full expected Euclid, BOSS, and DESI overlap region of approximately 6000 deg$^{2}$, the uncertainties attainable by clustering redshifts exceeds the Euclid requirement by at least a factor of three for both $n(z)$ models considered, although systematic biases limit the accuracy. Clustering redshifts are an extremely effective method for redshift calibration for Euclid if the sources of systematic biases can be determined and removed, or calibrated-out with sufficiently realistic simulations. We outline possible future work, in particular an extension to higher redshifts with quasar reference samples., Comment: 14 pages, 8 figures, accepted for publication in A&A
Published: 2022
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70. 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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71. Euclid: Testing the Copernican principle with next-generation surveys

Author: Camarena, D., Marra, V., Sakr, Z., Nesseris, S., Da Silva, A., Garcia-Bellido, J., Fleury, P., Lombriser, L., Martinelli, M., Martins, C. J. A. P., Mimoso, J., Sapone, D., Clarkson, C., Camera, S., Carbone, C., Casas, S., Ilić, S., Pettorino, V., Tutusaus, I., Aghanim, N., Altieri, B., Amara, A., Auricchio, N., Baldi, M., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Candini, G. P., Capobianco, V., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Degaudenzi, H., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kiessling, A., Kohley, R., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Marulli, F., Massey, R., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Polenta, G., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Rhodes, J., Riccio, G., Rix, Hans-Walter, Rossetti, E., Saglia, R., Sartoris, B., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Di Ferdinando, D., Scottez, V., and Tenti, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract: The Copernican principle, the notion that we are not at a special location in the Universe, is one of the cornerstones of modern cosmology and its violation would invalidate the Friedmann-Lema\^{\i}tre-Robertson-Walker (FLRW) metric, causing a major change in our understanding of the Universe. Thus, it is of fundamental importance to perform observational tests of this principle. We determine the precision with which future surveys will be able to test the Copernican principle and their ability to detect any possible violations. We forecast constraints on the inhomogeneous Lema\^{\i}tre-Tolman-Bondi model with a cosmological constant $\Lambda$ ($\Lambda$LTB), basically a cosmological constant $\Lambda$ and cold dark matter ($\Lambda$CDM) model, but endowed with a spherical inhomogeneity. We consider combinations of currently available data and simulated Euclid data, together with external data products, based on both $\Lambda$CDM and $\Lambda$LTB fiducial models. These constraints are compared to the expectations from the Copernican principle. When considering the $\Lambda$CDM fiducial model, we find that Euclid data, in combination with other current and forthcoming surveys, will improve the constraints on the Copernican principle by about $30\%$, with $\pm10\%$ variations depending on the observables and scales considered. On the other hand, when considering a $\Lambda$LTB fiducial model, we find that future Euclid data, combined with other current and forthcoming data sets, will be able to detect Gpc-scale inhomogeneities of contrast $-0.1$. Next-generation surveys, such as Euclid, will thoroughly test homogeneity at large scales, tightening the constraints on possible violations of the Copernican principle., Comment: 15 pages, 5 figures, 3 tables, v2 reflects version accepted for publication in A&A
Published: 2022
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72. 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

73. Euclid: Forecasts from the void-lensing cross-correlation

Author: Bonici, M., Carbone, C., Davini, S., Vielzeuf, P., Paganin, L., Cardone, V., Hamaus, N., Pisani, A., Hawken, A. J., Kovacs, A., Nadathur, S., Contarini, S., Verza, G., Tutusaus, I., Marulli, F., Moscardini, L., Aubert, M., Giocoli, C., Pourtsidou, A., Camera, S., Escoffier, S., Caminata, A., Martinelli, M., Pallavicini, M., Pettorino, V., Sakr, Z., Sapone, D., Testera, G., Tosi, S., Yankelevich, V., Amara, A., Auricchio, N., Baldi, M., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Carretero, J., Castellano, M., Cavuoti, S., Cledassou, R., 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., Ealet, A., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Gomez-Alvarez, P., Garilli, B., Gillis, B., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kummel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Massey, R., Medinaceli, E., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pires, S., Polenta, G., Poncet, M., Popa, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Rossetti, E., Saglia, R., Sartoris, B., Scodeggio, M., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Surace, C., Tallada-Crespi, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., and Andreon, S.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Euclid space telescope will survey a large dataset of cosmic voids traced by dense samples of galaxies. In this work we estimate its expected performance when exploiting angular photometric void clustering, galaxy weak lensing and their cross-correlation. To this aim, we implement a Fisher matrix approach tailored for voids from the Euclid photometric dataset and present the first forecasts on cosmological parameters that include the void-lensing correlation. We examine two different probe settings, pessimistic and optimistic, both for void clustering and galaxy lensing. We carry out forecast analyses in four model cosmologies, accounting for a varying total neutrino mass, $M_\nu$, and a dynamical dark energy (DE) equation of state, $w(z)$, described by the CPL parametrisation. We find that void clustering constraints on $h$ and $\Omega_b$ are competitive with galaxy lensing alone, while errors on $n_s$ decrease thanks to the orthogonality of the two probes in the 2D-projected parameter space. We also note that, as a whole, the inclusion of the void-lensing cross-correlation signal improves parameter constraints by $10-15\%$, and enhances the joint void clustering and galaxy lensing Figure of Merit (FoM) by $10\%$ and $25\%$, in the pessimistic and optimistic scenarios, respectively. Finally, when further combining with the spectroscopic galaxy clustering, assumed as an independent probe, we find that, in the most competitive case, the FoM increases by a factor of 4 with respect to the combination of weak lensing and spectroscopic galaxy clustering taken as independent probes. The forecasts presented in this work show that photometric void-clustering and its cross-correlation with galaxy lensing deserve to be exploited in the data analysis of the Euclid galaxy survey and promise to improve its constraining power, especially on $h$, $\Omega_b$, the neutrino mass, and the DE evolution., Comment: 22 pages, 9 figures - published in A&A
Published: 2022
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74. 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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75. Euclid: Fast two-point correlation function covariance through linear construction

Author: Keihanen, E., Lindholm, V., Monaco, P., Blot, L., Carbone, C., Kiiveri, K., Sánchez, A. G., Viitanen, A., Valiviita, J., Amara, A., Auricchio, N., Baldi, M., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kitching, T., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Marulli, F., Massey, R., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Morin, B., 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., Raison, F., Renzi, A., Rhodes, J., Romelli, E., Saglia, R., Sartoris, B., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., 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., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Maino, D., and de la Torre, S.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a method for fast evaluation of the covariance matrix for a two-point galaxy correlation function (2PCF) measured with the Landy-Szalay estimator. The standard way of evaluating the covariance matrix consists in running the estimator on a large number of mock catalogs, and evaluating their sample covariance. With large random catalog sizes (data-to-random objects ratio M>>1) the computational cost of the standard method is dominated by that of counting the data-random and random-random pairs, while the uncertainty of the estimate is dominated by that of data-data pairs. We present a method called Linear Construction (LC), where the covariance is estimated for small random catalogs of size M = 1 and M = 2, and the covariance for arbitrary M is constructed as a linear combination of these. We validate the method with PINOCCHIO simulations in range r = 20-200 Mpc/h, and show that the covariance estimate is unbiased. With M = 50 and with 2 Mpc/h bins, the theoretical speed-up of the method is a factor of 14. We discuss the impact on the precision matrix and parameter estimation, and derive a formula for the covariance of covariance., Comment: 17 pages, 11 figures
Published: 2022
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76. Euclid: Cosmological forecasts from the void size function

Author: Contarini, S., Verza, G., Pisani, A., Hamaus, N., Sahlén, M., Carbone, C., Dusini, S., Marulli, F., Moscardini, L., Renzi, A., Sirignano, C., Stanco, L., Aubert, M., Bonici, M., Castignani, G., Courtois, H. M., Escoffier, S., Guinet, D., Kovacs, A., Lavaux, G., Massara, E., Nadathur, S., Pollina, G., Ronconi, T., Ruppin, F., Sakr, Z., Veropalumbo, A., Wandelt, B. D., Amara, A., Auricchio, N., Baldi, M., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., 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., Dubath, F., Duncan, C. A. J., Dupac, X., Ealet, A., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S., Holmes, W., Hormuth, F., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Massey, R., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., 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., Pozzetti, L., Raison, F., Rhodes, J., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirri, G., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Maino, D., and Mei, S.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Euclid mission $-$ with its spectroscopic galaxy survey covering a sky area over $15\,000 \ \mathrm{deg}^2$ in the redshift range $0.9
Published: 2022
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77. 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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78. Euclid: Searching for pair-instability supernovae with the Deep Survey

Author: Moriya, T. J., Inserra, C., Tanaka, M., Cappellaro, E., Della Valle, M., Hook, I., Kotak, R., Longo, G., Mannucci, F., Mattila, S., Tao, C., Altieri, B., Amara, A., Auricchio, N., 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., 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., Ealet, A., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., McCracken, H. J., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Poncet, M., Popa, L., Raison, F., Rhodes, J., Riccio, G., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Scottez, V., and Morris, P. W.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract: Pair-instability supernovae are theorized supernovae that have not yet been observationally confirmed. They are predicted to exist in low-metallicity environments. Because overall metallicity becomes lower at higher redshifts, deep near-infrared transient surveys probing high-redshift supernovae are suitable to discover pair-instability supernovae. The Euclid satellite, which is planned to be launched in 2023, has a near-infrared wide-field instrument that is suitable for a high-redshift supernova survey. The Euclid Deep Survey is planned to make regular observations of three Euclid Deep Fields (40 deg2 in total) spanning the Euclid's 6 year primary mission period. While the observations of the Euclid Deep Fields are not frequent, we show that the predicted long duration of pair-instability supernovae would allow us to search for high-redshift pair-instability supernovae with the Euclid Deep Survey. Based on the current observational plan of the Euclid mission, we conduct survey simulations in order to estimate the expected numbers of pair-instability supernova discoveries. We find that up to several hundred pair-instability supernovae at z < ~ 3.5 can be discovered within the Euclid Deep Survey. We also show that pair-instability supernova candidates can be efficiently identified by their duration and color that can be determined with the current Euclid Deep Survey plan. We conclude that the Euclid mission can lead to the first confirmation of pair-instability supernovae if their event rates are as high as those predicted by recent theoretical studies. We also update the expected numbers of superluminous supernova discoveries in the Euclid Deep Survey based on the latest observational plan., Comment: 12 pages, 13 figures, 2 tables, accepted by Astronomy & Astrophysics
Published: 2022
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79. 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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80. Euclid: Covariance of weak lensing pseudo-$C_\ell$ estimates. Calculation, comparison to simulations, and dependence on survey geometry

Author: Upham, R. E., Brown, M. L., Whittaker, L., Amara, A., Auricchio, N., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillis, B., Giocoli, C., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Marggraf, O., Markovic, K., Marulli, F., 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., Poncet, M., Popa, L., Raison, F., Rhodes, J., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valenziano, L., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Baldi, M., Camera, S., Cardone, V. F., Fabbian, G., Polenta, G., Renzi, A., Joachimi, B., Hall, A., Loureiro, A., and Sellentin, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Statistics - Applications
Abstract: An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-$C_\ell$ estimates of tomographic cosmic shear power spectra. Using two existing publicly available codes in combination, we calculate the full covariance matrix, including mode-coupling contributions arising from both partial sky coverage and non-linear structure growth. For three different sky masks, we compare the theoretical covariance matrix to that estimated from publicly available N-body weak lensing simulations, finding good agreement. We find that as a more extreme sky cut is applied, a corresponding increase in both Gaussian off-diagonal covariance and non-Gaussian super-sample covariance is observed in both theory and simulations, in accordance with expectations. Studying the different contributions to the covariance in detail, we find that the Gaussian covariance dominates along the main diagonal and the closest off-diagonals, but further away from the main diagonal the super-sample covariance is dominant. Forming mock constraints in parameters describing matter clustering and dark energy, we find that neglecting non-Gaussian contributions to the covariance can lead to underestimating the true size of confidence regions by up to 70 per cent. The dominant non-Gaussian covariance component is the super-sample covariance, but neglecting the smaller connected non-Gaussian covariance can still lead to the underestimation of uncertainties by 10--20 per cent. A real cosmological analysis will require marginalisation over many nuisance parameters, which will decrease the relative importance of all cosmological contributions to the covariance, so these values should be taken as upper limits on the importance of each component., Comment: 15 pages, 8 figures; matches version accepted by A&A; code available at https://github.com/robinupham/shear_pcl_cov
Published: 2021
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81. Euclid preparation: XVIII. Cosmic Dawn Survey. Spitzer observations of the Euclid deep fields and calibration fields

Author: Moneti, Andrea, McCracken, H. J., Shuntov, M., Kauffmann, O. B., Capak, P., Davidzon, I., Ilbert, O., Scarlata, C., Toft, S., Weaver, J., Chary, R., Cuby, J., Faisst, A. L., Masters, D. C., McPartland, C., Mobasher, B., Sanders, D. B., Scaramella, R., Stern, D., Szapudi, I., Teplitz, H., Zalesky, L., Amara, A., Auricchio, N., Bodendorf, C., Bonino, D., Branchini, E., Brau-Nogue, S., Brescia, M., Brinchmann, J., 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., Costille, A., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hudelot, P., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kuemmel, 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., Maurogordato, S., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Rhodes, J., Rix, H., Roncarelli, M., Rossetti, E., Saglia, R., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespi, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Wang, Y., Welikala, N., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Camera, S., Gracia-Carpio, J., Medinaceli, E., Mei, S., Polenta, G., Romelli, E., Sureau, F., Tenti, M., Vassallo, T., Zacchei, A., Zucca, E., Baccigalupi, C., Balaguera-Antolinez, A., Bernardeau, F., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Colodro-Conde, C., Coupon, J., Courtois, H. M., Di Ferdinando, D., Farina, M., Finelli, F., Flose-Reimberg, P., Fotopoulou, S., Galeotta, S., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., Gozaliasl, G., Hook, I., Joachimi, B., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Lindholm, V., Mainetti, G., Maino, D., Maoli, R., Martinelli, M., Martinet, N., Maturi, M., Metcalf, R. B., Morgante, G., Morisset, N., Nucita, A., Patrizii, L., Potter, D., Renzi, A., Riccio, G., Sanchez, A. G., Sapone, D., Schirmer, M., Schultheis, M., Scottez, V., Sefusatti, E., Teyssier, R., Tubio, O., Tutusaus, I., Valiviita, J., Viel, M., and Hildebrandt, H.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a new infrared survey covering the three Euclid deep fields and four other Euclid calibration fields using Spitzer's Infrared Array Camera (IRAC). We have combined these new observations with all relevant IRAC archival data of these fields in order to produce the deepest possible mosaics of these regions. In total, these observations represent nearly 11% of the total Spitzer mission time. The resulting mosaics cover a total of approximately 71.5deg$^2$ in the 3.6 and 4.5um bands, and approximately 21.8deg$^2$ in the 5.8 and 8um bands. They reach at least 24 AB magnitude (measured to sigma, in a 2.5 arcsec aperture) in the 3.6um band and up to ~ 5 mag deeper in the deepest regions. The astrometry is tied to the Gaia astrometric reference system, and the typical astrometric uncertainty for sources with 16<[3.6]<19 is <0.15 arcsec. The photometric calibration is in excellent agreement with previous WISE measurements. We have extracted source number counts from the 3.6um band mosaics and they are in excellent agreement with previous measurements. Given that the Spitzer Space Telescope has now been decommissioned these mosaics are likely to be the definitive reduction of these IRAC data. This survey therefore represents an essential first step in assembling multi-wavelength data on the Euclid deep fields which are set to become some of the premier fields for extragalactic astronomy in the 2020s., Comment: 15 pages with 11 figures, approved by Euclid Consortium Publication Board and submitted to Astronomy and Astrophysics. Data products will become available via the IRSA website once the paper is accepted. This paper is a companion to "COSMOS2020: A panchromatic view of the Universe to z~10 from two complementary catalogs" by John Weaver et al., which is being posted in parallel
Published: 2021
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82. Euclid: Forecast constraints on consistency tests of the $\Lambda$CDM model

Author: Nesseris, S., Sapone, D., Martinelli, M., Camarena, D., Marra, V., Sakr, Z., Garcia-Bellido, J., Martins, C. J. A. P., Clarkson, C., Da Silva, A., Fleury, P., Lombriser, L., Mimoso, J. P., Casas, S., Pettorino, V., Tutusaus, I., Amara, A., Auricchio, N., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Jahnke, K., Kermiche, S., Kiessling, A., Kitching, T., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., 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., Poncet, M., Popa, L., Racca, G. D., Raison, F., Rhodes, J., Roncarelli, M., Saglia, R., Sartoris, B., 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., Wang, Y., Welikala, N., Zamorani, G., Zoubian, J., Andreon, S., Baldi, M., Camera, S., Medinaceli, E., Mei, S., and Renzi, A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology
Abstract: The standard cosmological model is based on the fundamental assumptions of a spatially homogeneous and isotropic universe on large scales. An observational detection of a violation of these assumptions at any redshift would immediately indicate the presence of new physics. We quantify the ability of the Euclid mission, together with contemporary surveys, to improve the current sensitivity of null tests of the canonical cosmological constant $\Lambda$ and the cold dark matter (LCDM) model in the redshift range $0
Published: 2021
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83. KiDS & Euclid: Cosmological implications of a pseudo angular power spectrum analysis of KiDS-1000 cosmic shear tomography

Author: Loureiro, A., Whittaker, L., Mancini, A. Spurio, Joachimi, B., Cuceu, A., Asgari, M., Stölzner, B., Tröster, T., Wright, A. H., Bilicki, M., Dvornik, A., Giblin, B., Heymans, C., Hildebrandt, H., Shan, H., Amara, A., Auricchio, N., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Cropper, M., Da Silva, A., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kuijken, K., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Meneghetti, M., Meylan, G., Moresco, M., Morin, B., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Poncet, M., Popa, L., Raison, F., Rhodes, J., Rix, H., Roncarelli, M., Saglia, R., Schneider, P., Secroun, A., 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., Wang, Y., Welikala, N., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Baldi, M., Camera, S., Farinelli, R., Polenta, G., and Tessore, N.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a tomographic weak lensing analysis of the Kilo Degree Survey Data Release 4 (KiDS-1000), using a new pseudo angular power spectrum estimator (pseudo-$C_{\ell}$) under development for the ESA Euclid mission. Over 21 million galaxies with shape information are divided into five tomographic redshift bins, ranging from 0.1 to 1.2 in photometric redshift. We measured pseudo-$C_{\ell}$ using eight bands in the multipole range $76<\ell<1500$ for auto- and cross-power spectra between the tomographic bins. A series of tests were carried out to check for systematic contamination from a variety of observational sources including stellar number density, variations in survey depth, and point spread function properties. While some marginal correlations with these systematic tracers were observed, there is no evidence of bias in the cosmological inference. B-mode power spectra are consistent with zero signal, with no significant residual contamination from E/B-mode leakage. We performed a Bayesian analysis of the pseudo-$C_{\ell}$ estimates by forward modelling the effects of the mask. Assuming a spatially flat $\Lambda$CDM cosmology, we constrained the structure growth parameter $S_8 = \sigma_8(\Omega_{\rm m}/0.3)^{1/2} = 0.754_{-0.029}^{+0.027}$. When combining cosmic shear from KiDS-1000 with baryon acoustic oscillation and redshift space distortion data from recent Sloan Digital Sky Survey (SDSS) measurements of luminous red galaxies, as well as the Lyman-$\alpha$ forest and its cross-correlation with quasars, we tightened these constraints to $S_8 = 0.771^{+0.006}_{-0.032}$. These results are in very good agreement with previous KiDS-1000 and SDSS analyses and confirm a $\sim 3\sigma$ tension with early-Universe constraints from cosmic microwave background experiments., Comment: 24 pages, 17 figures, Accepted by A&A
Published: 2021
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84. Euclid preparation: XIX. Impact of magnification on photometric galaxy clustering

Author: Lepori, F., Tutusaus, I., Viglione, C., Bonvin, C., Camera, S., Castander, F. J., Durrer, R., Fosalba, P., Jelic-Cizmek, G., Kunz, M., Adamek, J., Casas, S., Martinelli, M., Sakr, Z., Sapone, D., Amara, A., Auricchio, N., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., 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., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Ferriol, S., Franceschi, E., Fumana, M., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Hudelot, P., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rhodes, J., Roncarelli, M., Rossetti, E., Saglia, R., 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., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Fabbian, G., Graciá-Carpio, J., Maino, D., Medinaceli, E., Mei, S., Renzi, A., Romelli, E., Sureau, F., Vassallo, T., Zacchei, A., Zucca, E., Baccigalupi, C., Balaguera-Antolínez, A., Bernardeau, F., Biviano, A., Blanchard, A., Bolzonella, M., Borgani, S., Bozzo, E., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Colodro-Conde, C., Coupon, J., Courtois, H. M., Cuby, J. -G., Davini, S., de la Torre, S., Di Ferdinando, D., Farina, M., Ferreira, P. G., Finelli, F., Galeotta, S., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., Gozaliasl, G., Hook, I. M., Ilić, S., Joachimi, B., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Lindholm, V., Mainetti, G., Maoli, R., Martinet, N., Maturi, M., Metcalf, R. B., Monaco, P., Morgante, G., Nightingale, J., Nucita, A., Patrizii, L., Popa, V., Potter, D., Riccio, G., Sánchez, A. G, Schirmer, M., Schultheis, M., Scottez, V., Sefusatti, E., Tramacere, A., Valiviita, J., Viel, M., and Hildebrandt, H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We investigate the importance of lensing magnification for estimates of galaxy clustering and its cross-correlation with shear for the photometric sample of Euclid. Using updated specifications, we study the impact of lensing magnification on the constraints and the shift in the estimation of the best fitting cosmological parameters that we expect if this effect is neglected. We follow the prescriptions of the official Euclid Fisher matrix forecast for the photometric galaxy clustering analysis and the combination of photometric clustering and cosmic shear. The slope of the luminosity function (local count slope), which regulates the amplitude of the lensing magnification, and the galaxy bias have been estimated from the Euclid Flagship simulation.We find that magnification significantly affects both the best-fit estimation of cosmological parameters and the constraints in the galaxy clustering analysis of the photometric sample. In particular, including magnification in the analysis reduces the 1$\sigma$ errors on $\Omega_{\text{m},0}, w_{0}, w_a$ at the level of 20-35%, depending on how well we will be able to independently measure the local count slope. In addition, we find that neglecting magnification in the clustering analysis leads to shifts of up to 1.6$\sigma$ in the best-fit parameters. In the joint analysis of galaxy clustering, cosmic shear, and galaxy-galaxy lensing, magnification does not improve precision, but it leads to an up to 6$\sigma$ bias if neglected. Therefore, for all models considered in this work, magnification has to be included in the analysis of galaxy clustering and its cross-correlation with the shear signal ($3\times2$pt analysis) for an accurate parameter estimation., Comment: 26 pages, 11 figures. Version accepted for publication in A&A
Published: 2021
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85. Euclid: Forecasts from redshift-space distortions and the Alcock-Paczynski test with cosmic voids

Author: Hamaus, N., Aubert, M., Pisani, A., Contarini, S., Verza, G., Cousinou, M. -C., Escoffier, S., Hawken, A., Lavaux, G., Pollina, G., Wandelt, B. D., Weller, J., Bonici, M., Carbone, C., Guzzo, L., Kovacs, A., Marulli, F., Massara, E., Moscardini, L., Ntelis, P., Percival, W. J., Radinović, S., Sahlén, M., Sakr, Z., Sánchez, A. G., Winther, H. A., Auricchio, N., Awan, S., Bender, R., Bodendorf, C., 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., Conversi, L., Copin, Y., Corcione, L., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Marggraf, O., Markovic, K., Massey, R., Maurogordato, S., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Rebolo, R., Rhodes, J., Rix, H., Roncarelli, M., Rossetti, E., Saglia, R., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Starck, J. -L., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Wang, Y., Welikala, N., Zamorani, G., Zoubian, J., Andreon, S., Baldi, M., Camera, S., Mei, S., Neissner, C., and Romelli, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Euclid is poised to survey galaxies across a cosmological volume of unprecedented size, providing observations of more than a billion objects distributed over a third of the full sky. Approximately 20 million of these galaxies will have their spectroscopy available, allowing us to map the 3D large-scale structure of the Universe in great detail. This paper investigates prospects for the detection of cosmic voids therein and the unique benefit they provide for cosmology. In particular, we study the imprints of dynamic and geometric distortions of average void shapes and their constraining power on the growth of structure and cosmological distance ratios. To this end, we made use of the Flagship mock catalog, a state-of-the-art simulation of the data expected to be observed with Euclid. We arranged the data into four adjacent redshift bins, each of which contains about 11000 voids and estimated the stacked void-galaxy cross-correlation function in every bin. Fitting a linear-theory model to the data, we obtained constraints on $f/b$ and $D_M H$, where $f$ is the linear growth rate of density fluctuations, $b$ the galaxy bias, $D_M$ the comoving angular diameter distance, and $H$ the Hubble rate. In addition, we marginalized over two nuisance parameters included in our model to account for unknown systematic effects. With this approach, Euclid will be able to reach a relative precision of about 4% on measurements of $f/b$ and 0.5% on $D_M H$ in each redshift bin. Better modeling or calibration of the nuisance parameters may further increase this precision to 1% and 0.4%, respectively. Our results show that the exploitation of cosmic voids in Euclid will provide competitive constraints on cosmology even as a stand-alone probe. For example, the equation-of-state parameter $w$ for dark energy will be measured with a precision of about 10%, consistent with previous more approximate forecasts., Comment: 15 pages, 7 figures. Accepted by A&A (Oct. 31)
Published: 2021
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86. Euclid preparation: XVI. Exploring the ultra low-surface brightness Universe with Euclid/VIS

Author: Borlaff, A. S., Gómez-Alvarez, P., Altieri, B., Marcum, P. M., Vavrek, R., Laureijs, R., Kohley, R., Buitrago, F., Cuillandre, J. C., Duc, P. A., Venancio, L. M. Gaspar, Amara, A., Andreon, S., Auricchio, N., Azzollini, R., Baccigalupi, C., Balaguera-Antolínez, A., Baldi, M., Bardelli, S., Bender, R., Biviano, A., Bodendorf, C., Bonino, D., Bozzo, E., Branchini, E., Brescia, M., Brinchmann, J., Burigana, C., Cabanac, R., Camera, S., Candini, G. P., Capobianco, V., Cappi, A., Carbone, C., Carretero, J., Carvalho, C. S., Casas, S., Castander, F. J., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Cledassou, R., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Coupon, J., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Ferdinando, D., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Fabricius, M., Farina, M., Farrens, S., Ferreira, P. G., Ferriol, S., Finelli, F., Flose-Reimberg, P., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Ganga, K., Garilli, B., Gillis, B., Giocoli, C., Gozaliasl, G., Graciá-Carpio, J., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Jahnke, K., Keihanen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kirkpatrick, C. C., Kitching, T., Knapen, J. H., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Liebing, P., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maino, D., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Martínez-Delgado, D., Marulli, F., Massey, R., Maturi, M., Maurogordato, S., Medinaceli, E., Mei, S., Meneghetti, M., Merlin, E., Metcalf, R. B., Meylan, G., Moresco, M., Morgante, G., Moscardini, L., Munari, E., Nakajima, R., Neissner, C., Niemi, S. M., Nightingale, J. W., Nucita, A., Padilla, C., Paltani, S., Pasian, F., Patrizii, L., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Poncet, M., Popa, L., Potter, D., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rosset, C., Rossetti, E., Saglia, R., Sánchez, A. G., Sapone, D., Sauvage, M., Schneider, P., Scottez, V., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. L., Sureau, F., Tallada-Crespí, P., Taylor, A. N., Tenti, M., Tereno, I., Teyssier, R., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Valiviita, J., Vassallo, T., Viel, M., Wang, Y., Weller, J., Whittaker, L., Zacchei, A., Zamorani, G., and Zucca, E.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: While Euclid is an ESA mission specifically designed to investigate the nature of Dark Energy and Dark Matter, the planned unprecedented combination of survey area ($\sim15\,000$ deg$^2$), spatial resolution, low sky-background, and depth also make Euclid an excellent space observatory for the study of the low surface brightness Universe. Scientific exploitation of the extended low surface brightness structures requires dedicated calibration procedures yet to be tested. We investigate the capabilities of Euclid to detect extended low surface brightness structure by identifying and quantifying sky background sources and stray-light contamination. We test the feasibility of generating sky flat-fields to reduce large-scale residual gradients in order to reveal the extended emission of galaxies observed in the Euclid Survey. We simulate a realistic set of Euclid/VIS observations, taking into account both instrumental and astronomical sources of contamination, including cosmic rays, stray-light, zodiacal light, ISM, and the CIB, while simulating the effects of the presence of background sources in the FOV. We demonstrate that a combination of calibration lamps, sky flats and self-calibration would enable recovery of emission at a limiting surface brightness magnitude of $\mu=29.5^{+0.08}_{-0.27} $ mag arcsec$^{-2}$ ($3\sigma$, $10\times10$ arcsec$^2$) in the Wide Survey, reaching regions 2 magnitudes deeper in the Deep Surveys. Euclid/VIS has the potential to be an excellent low surface brightness observatory. Covering the gap between pixel-to-pixel calibration lamp flats and self-calibration observations for large scales, the application of sky flat-fielding will enhance the sensitivity of the VIS detector at scales of larger than 1 degree, up to the size of the FOV, enabling Euclid to detect extended surface brightness structures below $\mu=31$ mag arcsec$^{-2}$ and beyond., Comment: 23 pages, 13 figures, Euclid Consortium Key Project, accepted for publication in Astronomy & Astrophysics
Published: 2021
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87. Euclid preparation: I. The Euclid Wide Survey

Author: Scaramella, R., Amiaux, J., Mellier, Y., Burigana, C., Carvalho, C. S., Cuillandre, J. -C., Da Silva, A., Derosa, A., Dinis, J., Maiorano, E., Maris, M., Tereno, I., Laureijs, R., Boenke, T., Buenadicha, G., Dupac, X., Venancio, L. M. Gaspar, Gómez-Álvarez, P., Hoar, J., Alvarez, J. Lorenzo, Racca, G. D., Saavedra-Criado, G., Schwartz, J., Vavrek, R., Schirmer, M., Aussel, H., Azzollini, R., Cardone, V. F., Cropper, M., Ealet, A., Garilli, B., Gillard, W., Granett, B. R., Guzzo, L., Hoekstra, H., Jahnke, K., Kitching, T., Meneghetti, M., Miller, L., Nakajima, R., Niemi, S. M., Pasian, F., Percival, W. J., Sauvage, M., Scodeggio, M., Wachter, S., Zacchei, A., Aghanim, N., Amara, A., Auphan, T., Auricchio, N., Awan, S., Balestra, A., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brau-Nogue, S., Brescia, M., Candini, G. P., Capobianco, V., Carbone, C., Carlberg, R. G., Carretero, J., Casas, R., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Costille, A., Courbin, F., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Fourmanoit, N., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hudelot, P., Kermiche, S., Kiessling, A., Kilbinger, M., Kohley, R., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., Melchior, M., Merlin, E., Meylan, G., Mohr, J. J., Moresco, M., Morin, B., Moscardini, L., Munari, E., Nichol, R. C., Padilla, C., Paltani, S., Peacock, J., Pedersen, K., Pettorino, V., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Rhodes, J., Rix, H. -W., Roncarelli, M., Rossetti, E., Saglia, R., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. L., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., Toledo-Moreo, R., Torradeflot, F., Trifoglio, M., Valentijn, E. A., Valenziano, L., Kleijn, G. A. Verdoes, Wang, Y., Welikala, N., Weller, J., Wetzstein, M., Zamorani, G., Zoubian, J., Andreon, S., Baldi, M., Bardelli, S., Boucaud, A., Camera, S., Fabbian, G., Farinelli, R., Graciá-Carpio, J., Maino, D., Medinaceli, E., Mei, S., Neissner, C., Polenta, G., Renzi, A., Romelli, E., Rosset, C., Sureau, F., Tenti, M., Vassallo, T., Zucca, E., Baccigalupi, C., Balaguera-Antolínez, A., Battaglia, P., Biviano, A., Borgani, S., Bozzo, E., Cabanac, R., Cappi, A., Casas, S., Castignani, G., Colodro-Conde, C., Coupon, J., Courtois, H. M., Cuby, J., de la Torre, S., Desai, S., Di Ferdinando, D., Dole, H., Fabricius, M., Farina, M., Ferreira, P. G., Finelli, F., Flose-Reimberg, P., Fotopoulou, S., Galeotta, S., Ganga, K., Gozaliasl, G., Hook, I. M., Keihanen, E., Kirkpatrick, C. C., Liebing, P., Lindholm, V., Mainetti, G., Martinelli, M., Martinet, N., Maturi, M., McCracken, H. J., Metcalf, R. B., Morgante, G., Nightingale, J., Nucita, A., Patrizii, L., Potter, D., Riccio, G., Sánchez, A. G., Sapone, D., Schewtschenko, J. A., Schultheis, M., Scottez, V., Teyssier, R., Tutusaus, I., Valiviita, J., Viel, M., Vriend, W., and Whittaker, L.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Euclid is an ESA mission designed to constrain the properties of dark energy and gravity via weak gravitational lensing and galaxy clustering. It will carry out a wide area imaging and spectroscopy survey (EWS) in visible and near-infrared, covering roughly 15,000 square degrees of extragalactic sky on six years. The wide-field telescope and instruments are optimized for pristine PSF and reduced straylight, producing very crisp images. This paper presents the building of the Euclid reference survey: the sequence of pointings of EWS, Deep fields, Auxiliary fields for calibrations, and spacecraft movements followed by Euclid as it operates in a step-and-stare mode from its orbit around the Lagrange point L2. Each EWS pointing has four dithered frames; we simulate the dither pattern at pixel level to analyse the effective coverage. We use up-to-date models for the sky background to define the Euclid region-of-interest (RoI). The building of the reference survey is highly constrained from calibration cadences, spacecraft constraints and background levels; synergies with ground-based coverage are also considered. Via purposely-built software optimized to prioritize best sky areas, produce a compact coverage, and ensure thermal stability, we generate a schedule for the Auxiliary and Deep fields observations and schedule the RoI with EWS transit observations. The resulting reference survey RSD_2021A fulfills all constraints and is a good proxy for the final solution. Its wide survey covers 14,500 square degrees. The limiting AB magnitudes ($5\sigma$ point-like source) achieved in its footprint are estimated to be 26.2 (visible) and 24.5 (near-infrared); for spectroscopy, the H$_\alpha$ line flux limit is $2\times 10^{-16}$ erg cm$^{-2}$ s$^{-1}$ at 1600 nm; and for diffuse emission the surface brightness limits are 29.8 (visible) and 28.4 (near-infrared) mag arcsec$^{-2}$., Comment: 43 pages, 51 figures, submitted to A&A
Published: 2021
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88. Euclid Preparation: XIV. The Complete Calibration of the Color-Redshift Relation (C3R2) Survey: Data Release 3

Author: Euclid Collaboration, Stanford, S. A., Masters, D., Darvish, B., Stern, D., Cohen, J. G., Capak, P., Hernitschek, N., Davidzon, I., Rhodes, J., Sanders, D. B., Mobasher, B., Castander, F. J., Paltani, S., Aghanim, N., Amara, A., Auricchio, N., Balestra, A., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brinchmann, J., Capobianco, V., Carbone, C., Carretero, J., Casas, R., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Conselice, C. J., Corcione, L., Costille, A., Cropper, M., Degaudenzi, H., Douspis, M., Dubath, F., Dusini, S., Fosalba, P., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Garilli, B., Giocoli, C., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hudelot, P., Jahnke, K., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., Kummel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Marggraf, O., Markovic, K., Massey, R., Meneghetti, M., Meylan, G., Moscardini, L., Niemi, S. M., Padilla, C., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Roncarelli, M., Rossetti, E., Saglia, R., Scaramella, R., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Valentijn, E. A., Valenziano, L., Kleijn, G. A. Verdoes, Wang, Y., Zamorani, G., Zoubian, J., Brescia, M., Congedo, G., Conversi, L., Copin, Y., Kermiche, S., Kohley, R., Medinaceli, E., Mei, S., Moresco, M., Morin, B., Munari, E., Polenta, G., Sureau, F., Crespí, P. Tallada, Vassallo, T., Zacchei, A., Andreon, S., Aussel, H., Baccigalupi, C., Balaguera-Antolínez, A., Baldi, M., Bardelli, S., Biviano, A., Borsato, E., Bozzo, E., Burigana, C., Cabanac, R., Camera, S., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Colodro-Conde, C., Coupon, J., Courtois, H. M., Cuby, J. -G., Da Silva, A., de la Torre, S., Di Ferdinando, D., Duncan, C. A. J., Dupac, X., Fabricius, M., Farina, M., Farrens, S., Ferreira, P. G., Finelli, F., Flose-Reimberg, P., Fotopoulou, S., Galeotta, S., Ganga, K., Gillard, W., Gozaliasl, G., Graciá-Carpio, J., Keihanen, E., Kirkpatrick, C. C., Lindholm, V., Mainetti, G., Maino, D., Martinet, N., Marulli, F., Maturi, M., Maurogordato, S., Metcalf, R. B., Nakajima, R., Neissner, C., Nightingale, J. W., Nucita, A. A., Patrizii, L., Potter, D., Renzi, A., Riccio, G., Romelli, E., Sanchez, A. G., Sapone, D., Schirmer, M., Schultheis, M., Scottez, V., Stanco, L., Tenti, M., Teyssier, R., Torradeflot, F., Valiviita, J., Viel, M., Whittaker, L., and Zucca, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The Complete Calibration of the Color-Redshift Relation (C3R2) survey is obtaining spectroscopic redshifts in order to map the relation between galaxy color and redshift to a depth of i ~ 24.5 (AB). The primary goal is to enable sufficiently accurate photometric redshifts for Stage IV dark energy projects, particularly Euclid and the Roman Space Telescope, which are designed to constrain cosmological parameters through weak lensing. We present 676 new high-confidence spectroscopic redshifts obtained by the C3R2 survey in the 2017B-2019B semesters using the DEIMOS, LRIS, and MOSFIRE multi-object spectrographs on the Keck telescopes. Combined with the 4454 redshifts previously published by this project, the C3R2 survey has now obtained and published 5130 high-quality galaxy spectra and redshifts. If we restrict consideration to only the 0.2 < z(phot) < 2.6 range of interest for the Euclid cosmological goals, then with the current data release C3R2 has increased the spectroscopic redshift coverage of the Euclid color space from 51% (as reported by Masters et al. 2015) to the current 91%. Once completed and combined with extensive data collected by other spectroscopic surveys, C3R2 should provide the spectroscopic calibration set needed to enable photometric redshifts to meet the cosmology requirements for Euclid, and make significant headway toward solving the problem for Roman., Comment: 14 pages, 7 figures, 4 tables. Accepted for publication in The Astrophysical Journal Supplement. Survey website with links to the C3R2 redshift catalog and the spectroscopic data hosted by the Keck Observatory Archive can be found at https://sites.google.com/view/c3r2-survey/home
Published: 2021
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89. $Euclid$ preparation: XV. Forecasting cosmological constraints for the $Euclid$ and CMB joint analysis

Author: Euclid Collaboration, Ilić, S., Aghanim, N., Baccigalupi, C., Bermejo-Climent, J. R., Fabbian, G., Legrand, L., Paoletti, D., Ballardini, M., Archidiacono, M., Douspis, M., Finelli, F., Ganga, K., Hernández-Monteagudo, C., Lattanzi, M., Marinucci, D., Migliaccio, M., Carbone, C., Casas, S., Martinelli, M., Tutusaus, I., Natoli, P., Ntelis, P., Pagano, L., Wenzl, L., Gruppuso, A., Kitching, T., Langer, M., Mauri, N., Patrizii, L., Renzi, A., Sirri, G., Stanco, L., Tenti, M., Vielzeuf, P., Lacasa, F., Polenta, G., Yankelevich, V., Blanchard, A., Sakr, Z., Pourtsidou, A., Camera, S., Cardone, V. F., Kilbinger, M., Kunz, M., Markovic, K., Pettorino, V., Sánchez, A. G., Sapone, D., Amara, A., Auricchio, N., Bender, R., Bodendorf, C., 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., Costille, A., Cropper, M., Da Silva, A., Degaudenzi, H., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Fosalba, P., 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., Hoekstra, H., Holmes, W., Hormuth, F., Hudelot, P., Jahnke, K., Kermiche, S., Kiessling, A., Kohley, R., Kubik, B., Kümmel, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Marulli, F., Massey, R., Maurogordato, S., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Morin, B., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Rhodes, J., Roncarelli, M., Rossetti, E., Saglia, R., Scaramella, R., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Starck, J. L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Kleijn, G. A. Verdoes, Wang, Y., Welikala, N., Weller, J., Zamorani, G., Zoubian, J., Medinaceli, E., Mei, S., Rosset, C., Sureau, F., Vassallo, T., Zacchei, A., Andreon, S., Balaguera-Antolínez, A., Baldi, M., Bardelli, S., Biviano, A., Borgani, S., Bozzo, E., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Colodro-Conde, C., Coupon, J., Courtois, H. M., Cuby, J., de la Torre, S., Di Ferdinando, D., Dole, H., Farina, M., Ferreira, P. G., Flose-Reimberg, P., Galeotta, S., Gozaliasl, G., Graciá-Carpio, J., Keihanen, E., Kirkpatrick, C. C., Lindholm, V., Mainetti, G., Maino, D., Martinet, N., Maturi, M., Metcalf, R. B., Morgante, G., Neissner, C., Nightingale, J., Nucita, A. A., Potter, D., Riccio, G., Romelli, E., Schirmer, M., Schultheis, M., Scottez, V., Teyssier, R., Tramacere, A., Valiviita, J., Viel, M., Whittaker, L., and Zucca, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The combination and cross-correlation of the upcoming $Euclid$ data with cosmic microwave background (CMB) measurements is a source of great expectation since it will provide the largest lever arm of epochs, ranging from recombination to structure formation across the entire past light cone. In this work, we present forecasts for the joint analysis of $Euclid$ and CMB data on the cosmological parameters of the standard cosmological model and some of its extensions. This work expands and complements the recently published forecasts based on $Euclid$-specific probes, namely galaxy clustering, weak lensing, and their cross-correlation. With some assumptions on the specifications of current and future CMB experiments, the predicted constraints are obtained from both a standard Fisher formalism and a posterior-fitting approach based on actual CMB data. Compared to a $Euclid$-only analysis, the addition of CMB data leads to a substantial impact on constraints for all cosmological parameters of the standard $\Lambda$-cold-dark-matter model, with improvements reaching up to a factor of ten. For the parameters of extended models, which include a redshift-dependent dark energy equation of state, non-zero curvature, and a phenomenological modification of gravity, improvements can be of the order of two to three, reaching higher than ten in some cases. The results highlight the crucial importance for cosmological constraints of the combination and cross-correlation of $Euclid$ probes with CMB data., Comment: 20 pages, 8 figures, 5 tables, 1 appendix; updated to match version accepted by journal
Published: 2021
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90. Euclid preparation: XIII. Forecasts for galaxy morphology with the Euclid Survey using Deep Generative Models

Author: Euclid Collaboration, Bretonnière, H., Huertas-Company, M., Boucaud, A., Lanusse, F., Jullo, E., Merlin, E., Tuccillo, D., Castellano, M., Brinchmann, J., Conselice, C. J., Dole, H., Cabanac, R., Courtois, H. M., Castander, F. J., Duc, P. A., Fosalba, P., Guinet, D., Kruk, S., Kuchner, U., Serrano, S., Soubrie, E., Tramacere, A., Wang, L., Amara, A., Auricchio, N., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Capobianco, V., Carbone, C., Carretero, J., Cavuoti, S., Cimatti, A., Cledassou, R., Corcione, L., Costille, A., Degaudenzi, H., Douspis, M., Dubath, F., Dusini, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hudelot, P., Jahnke, K., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Massey, R., Melchior, M., Meneghetti, M., Meylan, G., Moscardini, L., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Rhodes, J., Roncarelli, M., Rossetti, E., Saglia, R., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Starck, J. -L., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Valentijn, E. A., Valenziano, L., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Baldi, M., Bardelli, S., Brau-Nogue, S., Brescia, M., Camera, S., Congedo, G., Conversi, L., Copin, Y., Duncan, C . A. J., Dupac, X., Farinelli, R., Gillis, B., Kermiche, S., Kohley, R., Marulli, F., Medinaceli, E., Mei, S., Moresco, M., Morin, B., Munari, E., Polenta, G., Romelli, E., Tallada-Crespí, P., Tenti, M., Torradeflot, F., Vassallo, T., Welikala, N., Zacchei, A., Zucca, E., Baccigalupi, C., Balaguera-Antolínez, A., Biviano, A., Borgani, S., Bozzo, E., Burigana, C., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Colodro-Conde, C., Coupon, J., Da Silva, A., de la Torre, S., Fabricius, M., Farina, M., Farrens, S., Ferreira, P. G., Flose-Reimberg, P., Fotopoulou, S., Galeotta, S., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., Gillard, W., Gozaliasl, G., Hook, I. M., Joachimi, B., Kansal, V., Kashlinsky, A., Keihanen, E., Kirkpatrick, C. C., Lindholm, V., Mainetti, G., Maino, D., Maoli, R., Martinelli, M., Martinet, N., Maurogordato, S., McCracken, H. J., Metcalf, R. B., Morgante, G., Morisset, N., Nakajima, R., Nightingale, J., Nucita, A., Patrizii, L., Potter, D., Renzi, A., Riccio, G., Sánchez, A. G., Sapone, D., Schirmer, M., Schultheis, M., Scottez, V., Sefusatti, E., Stanco, L., Teyssier, R., Tutusaus, I., Valiviita, J., Viel, M., Whittaker, L., and Knapen, J. H
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We present a machine learning framework to simulate realistic galaxies for the Euclid Survey. The proposed method combines a control on galaxy shape parameters offered by analytic models with realistic surface brightness distributions learned from real Hubble Space Telescope observations by deep generative models. We simulate a galaxy field of $0.4\,\rm{deg}^2$ as it will be seen by the Euclid visible imager VIS and show that galaxy structural parameters are recovered with similar accuracy as for pure analytic S\'ersic profiles. Based on these simulations, we estimate that the Euclid Wide Survey will be able to resolve the internal morphological structure of galaxies down to a surface brightness of $22.5\,\rm{mag}\,\rm{arcsec}^{-2}$, and $24.9\,\rm{mag}\,\rm{arcsec}^{-2}$ for the Euclid Deep Survey. This corresponds to approximately $250$ million galaxies at the end of the mission and a $50\,\%$ complete sample for stellar masses above $10^{10.6}\,\rm{M}_\odot$ (resp. $10^{9.6}\,\rm{M}_\odot$) at a redshift $z\sim0.5$ for the wide (resp. deep) survey. The approach presented in this work can contribute to improving the preparation of future high-precision cosmological imaging surveys by allowing simulations to incorporate more realistic galaxies., Comment: 22 pages, 21 figures (6 in appendinx). Accepted for publication to A&A. Change in the title for Euclid submission chronology coherence. Few changes for clarification
Published: 2021
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91. Euclid preparation: XI. Mean redshift determination from galaxy redshift probabilities for cosmic shear tomography

Author: Euclid Collaboration, Ilbert, O., de la Torre, S., Martinet, N., Wright, A. H., Paltani, S., Laigle, C., Davidzon, I., Jullo, E., Hildebrandt, H., Masters, D. C., Amara, A., Conselice, C. J., Andreon, S., Auricchio, N., Azzollini, R., Baccigalupi, C., Balaguera-Antolínez, A., Baldi, M., Balestra, A., Bardelli, S., Bender, R., Biviano, A., Bodendorf, C., Bonino, D., Borgani, S., Boucaud, A., Bozzo, E., Branchini, E., Brescia, M., Burigana, C., Cabanac, R., Camera, S., Capobianco, V., Cappi, A., Carbone, C., Carretero, J., Carvalho, C. S., Casas, S., Castander, F. J., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Cledassou, R., Colodro-Conde, C., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Costille, A., Coupon, J., Courtois, H. M., Cropper, M., Cuby, J., Da Silva, A., Degaudenzi, H., Di Ferdinando, D., Dubath, F., Duncan, C., Dupac, X., Dusini, S., Ealet, A., Fabricius, M., Farrens, S., Ferreira, P. G., Finelli, F., Fosalba, P., Fotopoulou, S., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Gozaliasl, G., Graciá-Carpio, J., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Jahnke, K., Keihanen, E., Kermiche, S., Kiessling, A., Kirkpatrick, C. C., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maino, D., Maiorano, E., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maturi, M., Mauri, N., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Metcalf, R. Benton, Moresco, M., Morin, B., Moscardini, L., Munari, E., Nakajima, R., Neissner, C., Niemi, S., Nightingale, J., Padilla, C., Pasian, F., Patrizii, L., Pedersen, K., Pello, R., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L., Potter, D., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sánchez, A. G., Sapone, D., Schneider, P., Schrabback, T., Scottez, V., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Sureau, F., Crespí, P. Tallada, Tenti, M., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tramacere, A., Valentijn, E. A., Valenziano, L., Valiviita, J., Vassallo, T., Wang, Y., Welikala, N., Weller, J., Whittaker, L., Zacchei, A., Zamorani, G., Zoubian, J., and Zucca, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The analysis of weak gravitational lensing in wide-field imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on the accurate knowledge of the galaxy mean redshift $\langle z \rangle$. We investigate the possibility of measuring $\langle z \rangle$ with an accuracy better than $0.002\,(1+z)$, in ten tomographic bins spanning the redshift interval $0.299.8\%$. The zPDF approach could also be successful if we debias the zPDF using a spectroscopic training sample. This approach requires deep imaging data, but is weakly sensitive to spectroscopic redshift failures in the training sample. We improve the debiasing method and confirm our finding by applying it to real-world weak-lensing data sets (COSMOS and KiDS+VIKING-450)., Comment: 21 pages, 10 figures, accepted in A&A
Published: 2021
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92. Euclid preparation: IX. EuclidEmulator2 -- Power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations

Author: Euclid Collaboration, Knabenhans, M., Stadel, J., Potter, D., Dakin, J., Hannestad, S., Tram, T., Marelli, S., Schneider, A., Teyssier, R., Andreon, S., Auricchio, N., Baccigalupi, C., Balaguera-Antolínez, A., Baldi, M., Bardelli, S., Battaglia, P., Bender, R., Biviano, A., Bodendorf, C., Bozzo, E., Branchini, E., Brescia, M., Burigana, C., Cabanac, R., Camera, S., Capobianco, V., Cappi, A., Carbone, C., Carretero, J., Carvalho, C. S., Casas, R., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cledassou, R., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Coupon, J., Courtois, H. M., Da Silva, A., de la Torre, S., Di Ferdinando, D., Duncan, C. A. J., Dupac, X., Fabbian, G., Farrens, S., Ferreira, P. G., Finelli, F., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Giocoli, C., Gozaliasl, G., Graciá-Carpio, J., Grupp, F., Guzzo, L., Holmes, W., Hormuth, F., Israel, H., Jahnke, K., Keihanen, E., Kermiche, S., Kirkpatrick, C. C., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maino, D., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Mauri, N., Maurogordato, S., Medinaceli, E., Meneghetti, M., Metcalf, B., Meylan, G., Moresco, M., Morin, B., Moscardini, L., Munari, E., Neissner, C., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Patrizii, L., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sánchez, A. G., Sapone, D., Schneider, P., Scottez, V., Secroun, A., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Sureau, F., Crespí, P. Tallada, Taylor, A. N., Tenti, M., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valenziano, L., Valiviita, J., Vassallo, T., Viel, M., Wang, Y., Welikala, N., Whittaker, L., Zacchei, A., and Zucca, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a new, updated version of the EuclidEmulator (called EuclidEmulator2), a fast and accurate predictor for the nonlinear correction of the matter power spectrum. Percent-level accurate emulation is now supported in the eight-dimensional parameter space of $w_0w_a$CDM$+\sum m_\nu$models between redshift $z=0$ and $z=3$ for spatial scales within the range 0.01 $h$/Mpc $\leq k \leq$ 10 $h$/Mpc. In order to achieve this level of accuracy, we have had to improve the quality of the underlying N-body simulations used as training data: (1) we use self-consistent linear evolution of non-dark matter species such as massive neutrinos, photons, dark energy and the metric field, (2) we perform the simulations in the so-called N-body gauge, which allows one to interpret the results in the framework of general relativity, (3) we run over 250 high-resolution simulations with $3000^3$ particles in boxes of 1 (Gpc/$h$)${}^3$ volumes based on paired-and-fixed initial conditions and (4) we provide a resolution correction that can be applied to emulated results as a post-processing step in order to drastically reduce systematic biases on small scales due to residual resolution effects in the simulations. We find that the inclusion of the dynamical dark energy parameter $w_a$ significantly increases the complexity and expense of creating the emulator. The high fidelity of EuclidEmulator2 is tested in various comparisons against N-body simulations as well as alternative fast predictors like Halofit, HMCode and CosmicEmu. A blind test is successfully performed against the Euclid Flagship v2.0 simulation. Nonlinear correction factors emulated with EuclidEmulator2 are accurate at the level of 1% or better for 0.01 $h$/Mpc $\leq k \leq$ 10 $h$/Mpc and $z\leq3$ compared to high-resolution dark matter only simulations. EuclidEmulator2 is publicly available at https://github.com/miknab/EuclidEmulator2 ., Comment: 28 pages, 19 figures, submitted to MNRAS
Published: 2020
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93. Euclid preparation: X. The Euclid photometric-redshift challenge

Author: Euclid Collaboration, Desprez, G., Paltani, S., Coupon, J., Almosallam, I., Alvarez-Ayllon, A., Amaro, V., Brescia, M., Brodwin, M., Cavuoti, S., De Vicente-Albendea, J., Fotopoulou, S., Hatfield, P. W., Hartley, W. G., Ilbert, O., Jarvis, M. J., Longo, G., Saha, R., Speagle, J. S., Tramacere, A., Castellano, M., Dubath, F., Galametz, A., Kuemmel, M., Laigle, C., Merlin, E., Mohr, J. J., Pilo, S., Salvato, M., Rau, M. M., Andreon, S., Auricchio, N., Baccigalupi, C., Balaguera-Antolínez, A., Baldi, M., Bardelli, S., Bender, R., Biviano, A., Bodendorf, C., Bonino, D., Bozzo, E., Branchini, E., Brinchmann, J., Burigana, C., Cabanac, R., Camera, S., Capobianco, V., Cappi, A., Carbone, C., Carretero, J., Carvalho, C. S., Casas, R., Casas, S., Castander, F. J., Castignani, G., Cimatti, A., Cledassou, R., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courtois, H. M., Cuby, J. -G., Da Silva, A., de la Torre, S., Degaudenzi, H., Di Ferdinando, D., Douspis, M., Duncan, C. A. J., Dupac, X., Ealet, A., Fabbian, G., Fabricius, M., Farrens, S., Ferreira, P. G., Finelli, F., Fosalba, P., Fourmanoit, N., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Gozaliasl, G., Graciá-Carpio, J., Grupp, F., Guzzo, L., Hailey, M., Haugan, S. V. H., Holmes, W., Hormuth, F., Humphrey, A., Jahnke, K., Keihanen, E., Kermiche, S., Kilbinger, M., Kirkpatrick, C. C., Kitching, T. D., Kohley, R., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maino, D., Maiorano, E., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maturi, M., Mauri, N., Maurogordato, S., Medinaceli, E., Mei, S., Meneghetti, M., Metcalf, R. Benton, Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S., Padilla, C., Pasian, F., Patrizii, L., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L., Potter, D., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Rossetti, E., Saglia, R., Sapone, D., Schneider, P., Scottez, V., Secroun, A., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Stern, D., Sureau, F., Crespí, P. Tallada, Tavagnacco, D., Taylor, A. N., Tenti, M., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valenziano, L., Valiviita, J., Vassallo, T., Viel, M., Wang, Y., Welikala, N., Whittaker, L., Zacchei, A., Zamorani, G., Zoubian, J., and Zucca, E.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo-$z$s at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2--2.6 redshift range that the Euclid mission will probe. We design a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data are divided into two samples: one calibration sample for which photometry and redshifts are provided to the participants; and the validation sample, containing only the photometry, to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates sources they consider unfit for use in cosmological analyses. The performance of each method is assessed through a set of informative metrics, using cross-matched spectroscopic and highly-accurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, sources for which the photo-z deviates by more than 0.15(1+z) from the spectroscopic-redshift (spec-z). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. [abridged], Comment: Accepted in A&A, 25 pages, 13 figures, 7 tables
Published: 2020
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94. Euclid preparation: VIII. The Complete Calibration of the Colour-Redshift Relation survey: VLT/KMOS observations and data release

Author: Euclid Collaboration, Guglielmo, V., Saglia, R., Castander, F. J., Galametz, A., Paltani, S., Bender, R., Bolzonella, M., Capak, P., Ilbert, O., Masters, D. C., Stern, D., Andreon, S., Auricchio, N., Balaguera-Antolínez, A., Baldi, M., Bardelli, S., Biviano, A., Bodendorf, C., Bonino, D., Bozzo, E., Branchini, E., Brau-Nogue, S., Brescia, M., Burigana, C., Cabanac, R. A., Camera, S., Capobianco, V., Cappi, A., Carbone, C., Carretero, J., Carvalho, C. S., Casas, R., 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., Costille, A., Coupon, J., Courtois, H. M., Cropper, M., Da Silva, A., de la Torre, S., Di Ferdinando, D., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Fabricius, M., Farrens, S., Ferreira, P. G., Fotopoulou, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Gozaliasl, G., Graciá-Carpio, J., Grupp, F., Guzzo, L., Hildebrandt, H., Hoekstra, H., Hormuth, F., Israel, H., Jahnke, K., Keihanen, E., Kermiche, S., Kilbinger, M., Kirkpatrick, C. C., Kitching, T., Kubik, B., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lloro, I., Maino, D., Maiorano, E., Maraston, C., Marggraf, O., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Meneghetti, M., Metcalf, R. Benton, Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Neissner, C., Niemi, S., Nucita, A. A., Padilla, C., Pasian, F., Patrizii, L., Pocino, A., Poncet, M., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Sanchez, A. G., Sapone, D., Schneider, P., Scottez, V., Secroun, A., Serrano, S., Sirignano, C., Sirri, G., Sureau, F., Tallada-Crespi, P., Tavagnacco, D., Taylor, A. N., Tenti, M., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tramacere, A., Valenziano, L., Vassallo, T., Wang, Y., Welikala, N., Wetzstein, M., Whittaker, L., Zacchei, A., Zamorani, G., Zoubian, J., and Zucca, E.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Complete Calibration of the Colour-Redshift Relation survey (C3R2) is a spectroscopic effort involving ESO and Keck facilities designed to empirically calibrate the galaxy colour-redshift relation - P(z|C) to the Euclid depth (i_AB=24.5) and is intimately linked to upcoming Stage IV dark energy missions based on weak lensing cosmology. The aim is to build a spectroscopic calibration sample that is as representative as possible of the galaxies of the Euclid weak lensing sample. In order to minimise the number of spectroscopic observations to fill the gaps in current knowledge of the P(z|C), self-organising map (SOM) representations of the galaxy colour space have been constructed. Here we present the first results of an ESO@ VLT Large Programme approved in the context of C3R2, which makes use of the two VLT optical and near-infrared multi-object spectrographs, FORS2 and KMOS. This paper focuses on high-quality spectroscopic redshifts of high-z galaxies observed with the KMOS spectrograph in the H- and K-bands. A total of 424 highly-reliable z are measured in the 1.3<=z<=2.5 range, with total success rates of 60.7% in the H-band and 32.8% in the K-band. The newly determined z fill 55% of high and 35% of lower priority empty SOM grid cells. We measured Halpha fluxes in a 1."2 radius aperture from the spectra of the spectroscopically confirmed galaxies and converted them into star formation rates. In addition, we performed an SED fitting analysis on the same sample in order to derive stellar masses, E(B-V), total magnitudes, and SFRs. We combine the results obtained from the spectra with those derived via SED fitting, and we show that the spectroscopic failures come from either weakly star-forming galaxies (at z<1.7, i.e. in the H-band) or low S/N spectra (in the K-band) of z>2 galaxies., Comment: 21 pages, 12 figures
Published: 2020
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95. Euclid preparation: VI. Verifying the Performance of Cosmic Shear Experiments

Author: Euclid Collaboration, Paykari, P., Kitching, T. D., Hoekstra, H., Azzollini, R., Cardone, V. F., Cropper, M., Duncan, C. A. J., Kannawadi, A., Miller, L., Aussel, H., Conti, I. F., Auricchio, N., Baldi, M., Bardelli, S., Biviano, A., Bonino, D., Borsato, E., Bozzo, E., Branchini, E., Brau-Nogue, S., Brescia, M., Brinchmann, J., Burigana, C., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Charles, Y., Cledassou, R., Colodro-Conde, C., Congedo, G., Conselice, C., Conversi, L., Copin, Y., Coupon, J., Courtois, H. M., Da Silva, A., Dupac, X., Fabbian, G., Farrens, S., Ferreira, P. G., Fosalba, P., Fourmanoit, N., Frailis, M., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B. R., Giocoli, C., Gracia-Carpio, J., Grupp, F., Hormuth, F., Ilic, S., Israel, H., Jahnke, K., Keihanen, E., Kermiche, S., Kilbinger, M., Kirkpatrick, C. C., Kubik, B., Kunz, M., Kurki-Suonio, H., Lacasa, F., Laureijs, R., Mignant, D. Le, Ligori, S., Lilje, P. B., Lloro, I., Maciaszek, T., Maiorano, E., Marggraf, O., Martinelli, M., Martinet, N., Massey, F. Marulli R., Mauri, N., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Metcalf, R. B., Moresco, M., Moscardini, L., Munari, E., Neissner, C., Nichol, R. C., Niemi, S., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Pettorino, V., Pires, S., Polenta, G., Pourtsidou, A., Raison, F., Renzi, A., Rhodes, J., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sánchez, A. G., Sapone, D., Scaramella, R., Schneider, P., Schrabback, T., Scottez, V., Secroun, A., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Sureau, F., Tallada-Crespí, P., Taylor, A., Tenti, M., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vannier, M., Vassallo, T., Zoubian, J., and Zucca, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Our aim is to quantify the impact of systematic effects on the inference of cosmological parameters from cosmic shear. We present an end-to-end approach that introduces sources of bias in a modelled weak lensing survey on a galaxy-by-galaxy level. Residual biases are propagated through a pipeline from galaxy properties (one end) through to cosmic shear power spectra and cosmological parameter estimates (the other end), to quantify how imperfect knowledge of the pipeline changes the maximum likelihood values of dark energy parameters. We quantify the impact of an imperfect correction for charge transfer inefficiency (CTI) and modelling uncertainties of the point spread function (PSF) for Euclid, and find that the biases introduced can be corrected to acceptable levels., Comment: 18 pages. Submitted to A&A. Comments Welcome
Published: 2019
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96. Euclid preparation: VII. Forecast validation for Euclid cosmological probes

Author: Euclid Collaboration, Blanchard, A., Camera, S., Carbone, C., Cardone, V. F., Casas, S., Clesse, S., Ilić, S., Kilbinger, M., Kitching, T., Kunz, M., Lacasa, F., Linder, E., Majerotto, E., Markovič, K., Martinelli, M., Pettorino, V., Pourtsidou, A., Sakr, Z., Sánchez, A. G., Sapone, D., Tutusaus, I., Yahia-Cherif, S., Yankelevich, V., Andreon, S., Aussel, H., Balaguera-Antolínez, A., Baldi, M., Bardelli, S., Bender, R., Biviano, A., Bonino, D., Boucaud, A., Bozzo, E., Branchini, E., Brau-Nogue, S., Brescia, M., Brinchmann, J., Burigana, C., Cabanac, R., Capobianco, V., Cappi, A., Carretero, J., Carvalho, C. S., Casas, R., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Coupon, J., Courtois, H. M., Cropper, M., Da Silva, A., de la Torre, S., Di Ferdinando, D., Dubath, F., Ducret, F., Duncan, C. A. J., Dupac, X., Dusini, S., Fabbian, G., Fabricius, M., Farrens, S., Fosalba, P., Fotopoulou, S., Fourmanoit, N., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Graciá-Carpio, J., Grupp, F., Guzzo, L., Hoekstra, H., Hormuth, F., Israel, H., Jahnke, K., Keihanen, E., Kermiche, S., Kirkpatrick, C. C., Kohley, R., Kubik, B., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maino, D., Maiorano, E., Marggraf, O., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Mellier, Y., Metcalf, B., Metge, J. J., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nichol, R. C., Niemi, S., Nucita, A. A., Padilla, C., Paltani, S., Pasian, F., Percival, W. J., Pires, S., Polenta, G., Poncet, M., Pozzetti, L., Racca, G. D., Raison, F., Renzi, A., Rhodes, J., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Schneider, P., Scottez, V., Secroun, A., Sirri, G., Stanco, L., Starck, J. -L., Sureau, F., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tenti, M., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valenziano, L., Vassallo, T., Kleijn, G. A. Verdoes, Viel, M., Wang, Y., Zacchei, A., Zoubian, J., and Zucca, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Euclid space telescope will measure the shapes and redshifts of galaxies to reconstruct the expansion history of the Universe and the growth of cosmic structures. Estimation of the expected performance of the experiment, in terms of predicted constraints on cosmological parameters, has so far relied on different methodologies and numerical implementations, developed for different observational probes and for their combination. In this paper we present validated forecasts, that combine both theoretical and observational expertise for different cosmological probes. This is presented to provide the community with reliable numerical codes and methods for Euclid cosmological forecasts. We describe in detail the methodology adopted for Fisher matrix forecasts, applied to galaxy clustering, weak lensing and their combination. We estimate the required accuracy for Euclid forecasts and outline a methodology for their development. We then compare and improve different numerical implementations, reaching uncertainties on the errors of cosmological parameters that are less than the required precision in all cases. Furthermore, we provide details on the validated implementations that can be used by the reader to validate their own codes if required. We present new cosmological forecasts for Euclid. We find that results depend on the specific cosmological model and remaining freedom in each setup, i.e. flat or non-flat spatial cosmologies, or different cuts at nonlinear scales. The validated numerical implementations can now be reliably used for any setup. We present results for an optimistic and a pessimistic choice of such settings. We demonstrate that the impact of cross-correlations is particularly relevant for models beyond a cosmological constant and may allow us to increase the dark energy Figure of Merit by at least a factor of three., Comment: 74 pages, 13 figures, 18 tables. Acknowledgements include Authors' contributions. Abstract abridged. Version accepted for publication in A&A
Published: 2019
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97. Euclid preparation: V. Predicted yield of redshift 7<z<9 quasars from the wide survey

Author: Euclid Collaboration, Barnett, R., Warren, S. J., Mortlock, D. J., Cuby, J. -G., Conselice, C., Hewett, P. C., Willott, C. J., Auricchio, N., Balaguera-Antolínez, A., Baldi, M., Bardelli, S., Bellagamba, F., Bender, R., Biviano, A., Bonino, D., Bozzo, E., Branchini, E., Brescia, M., Brinchmann, J., Burigana, C., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Carvalho, C. S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Clédassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Coupon, J., Courtois, H. M., Cropper, M., Da Silva, A., Duncan, C. A. J., Dusini, S., Ealet, A., Farrens, S., Fosalba, P., Fotopoulou, S., Fourmanoit, N., Frailis, M., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B. R., Graciá-Carpio, J., Grupp, F., Hoekstra, H., Hormuth, F., Israel, H., Jahnke, K., Kermiche, S., Kilbinger, M., Kirkpatrick, C. C., Kitching, T., Kohley, R., Kubik, B., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Martinet, N., Marulli, F., Massey, R., Mauri, N., Medinaceli, E., Mei, S., Mellier, Y., Metcalf, R. B., Metge, J. J., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Neissner, C., Niemi, S. M., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Paykari, P., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Rix, H. -W., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Scaramella, R., Schneider, P., Scottez, V., Secroun, A., Serrano, S., Sirri, G., Stanco, L., Sureau, F., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tenti, M., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valenziano, L., Vassallo, T., Wang, Y., Zacchei, A., Zamorani, G., Zoubian, J., and Zucca, E.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We provide predictions of the yield of $78$ may be selected from Euclid $OYJH$ photometry alone, but selection over the redshift interval $77.5$ should be found in the DR1 data release, expected in 2024. It will be possible to determine the bright-end slope of the QLF, $7
Published: 2019
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98. Euclid preparation XXXVII. Galaxy colour selections with Euclid and ground photometry for cluster weak-lensing analyses

Author: Lesci, G, Sereno, M, Radovich, M, Castignani, G, Bisigello, L, Marulli, F, Moscardini, L, Baumont, L, Covone, G, Farrens, S, Giocoli, C, Ingoglia, L, Miranda La Hera, S, 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, Castellano, M, Cavuoti, S, Cimatti, A, Congedo, G, Conselice, C, Conversi, L, Copin, Y, Corcione, L, Courbin, F, Courtois, H, Da Silva, A, Degaudenzi, H, Di Giorgio, A, Dinis, J, Dubath, F, Duncan, C, 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, Hook, I, Hormuth, F, Hornstrup, A, Hudelot, P, Jahnke, K, Kummel, M, Kermiche, S, Kiessling, A, Kilbinger, M, Kubik, B, Kunz, M, Kurki-Suonio, H, Ligori, S, Lilje, P, 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, 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, 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, Tallada-Crespi, P, Taylor, A, Teplitz, H, Tereno, I, Toledo-Moreo, R, Torradeflot, F, Tutusaus, I, Valentijn, E, 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, Gracia-Carpio, J, Marcin, S, Mauri, N, Neissner, C, Nucita, A, Sakr, Z, Scottez, V, Tenti, M, Viel, M, Wiesmann, M, Akrami, Y, Anselmi, S, Baccigalupi, C, Ballardini, M, Borgani, S, Borlaff, A, Bruton, S, Burigana, C, Cabanac, R, Calabro, A, Cappi, A, Carvalho, C, Castro, T, Canas-Herrera, G, Chambers, K, Cooray, A, Coupon, J, Cucciati, O, Davini, S, De La Torre, S, De Lucia, G, Desprez, G, Di Domizio, S, Dole, H, Diaz-Sanchez, A, Escartin Vigo, J, Escoffier, S, Ferrero, I, Finelli, F, Gabarra, L, Ganga, K, Garcia-Bellido, J, Giacomini, F, Gozaliasl, G, Gwyn, S, Hildebrandt, H, Huertas-Company, M, Jimenez Munoz, A, Kajava, J, Kansal, V, Kirkpatrick, C, Legrand, L, Loureiro, A, MacIas-Perez, J, Magliocchetti, M, Mainetti, G, Maoli, R, Martinelli, M, Martins, C, Matthew, S, Maturi, M, Maurin, L, Metcalf, R, Migliaccio, M, Monaco, P, Morgante, G, Nadathur, S, Patrizii, L, Pezzotta, A, Porciani, C, Potter, D, Pontinen, M, Reimberg, P, Rocci, P, Sanchez, A, Schneider, A, Schultheis, M, Sefusatti, E, Simon, P, Spurio Mancini, A, Stanford, S, Steinwagner, J, Testera, G, Teyssier, R, Toft, S, Tosi, S, Troja, A, Tucci, M, Valiviita, J, Vergani, D, 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., Miranda La Hera S., 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., Kummel 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-Crespi 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., Gracia-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., Canas-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., Diaz-Sanchez A., Escartin Vigo J. A., Escoffier S., Ferrero I., Finelli F., Gabarra L., Ganga K., Garcia-Bellido J., Giacomini F., Gozaliasl G., Gwyn S., Hildebrandt H., Huertas-Company M., Jimenez Munoz A., 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., Pontinen M., Reimberg P., Rocci P. -F., Sanchez A. G., Schneider A., Schultheis M., Sefusatti E., Simon P., Spurio Mancini A., Stanford S. A., Steinwagner J., Testera G., Teyssier R., Toft S., Tosi S., Troja A., Tucci M., Valiviita J., Vergani D., Lesci, G, Sereno, M, Radovich, M, Castignani, G, Bisigello, L, Marulli, F, Moscardini, L, Baumont, L, Covone, G, Farrens, S, Giocoli, C, Ingoglia, L, Miranda La Hera, S, 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, Castellano, M, Cavuoti, S, Cimatti, A, Congedo, G, Conselice, C, Conversi, L, Copin, Y, Corcione, L, Courbin, F, Courtois, H, Da Silva, A, Degaudenzi, H, Di Giorgio, A, Dinis, J, Dubath, F, Duncan, C, 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, Hook, I, Hormuth, F, Hornstrup, A, Hudelot, P, Jahnke, K, Kummel, M, Kermiche, S, Kiessling, A, Kilbinger, M, Kubik, B, Kunz, M, Kurki-Suonio, H, Ligori, S, Lilje, P, 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, 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, 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, Tallada-Crespi, P, Taylor, A, Teplitz, H, Tereno, I, Toledo-Moreo, R, Torradeflot, F, Tutusaus, I, Valentijn, E, 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, Gracia-Carpio, J, Marcin, S, Mauri, N, Neissner, C, Nucita, A, Sakr, Z, Scottez, V, Tenti, M, Viel, M, Wiesmann, M, Akrami, Y, Anselmi, S, Baccigalupi, C, Ballardini, M, Borgani, S, Borlaff, A, Bruton, S, Burigana, C, Cabanac, R, Calabro, A, Cappi, A, Carvalho, C, Castro, T, Canas-Herrera, G, Chambers, K, Cooray, A, Coupon, J, Cucciati, O, Davini, S, De La Torre, S, De Lucia, G, Desprez, G, Di Domizio, S, Dole, H, Diaz-Sanchez, A, Escartin Vigo, J, Escoffier, S, Ferrero, I, Finelli, F, Gabarra, L, Ganga, K, Garcia-Bellido, J, Giacomini, F, Gozaliasl, G, Gwyn, S, Hildebrandt, H, Huertas-Company, M, Jimenez Munoz, A, Kajava, J, Kansal, V, Kirkpatrick, C, Legrand, L, Loureiro, A, MacIas-Perez, J, Magliocchetti, M, Mainetti, G, Maoli, R, Martinelli, M, Martins, C, Matthew, S, Maturi, M, Maurin, L, Metcalf, R, Migliaccio, M, Monaco, P, Morgante, G, Nadathur, S, Patrizii, L, Pezzotta, A, Porciani, C, Potter, D, Pontinen, M, Reimberg, P, Rocci, P, Sanchez, A, Schneider, A, Schultheis, M, Sefusatti, E, Simon, P, Spurio Mancini, A, Stanford, S, Steinwagner, J, Testera, G, Teyssier, R, Toft, S, Tosi, S, Troja, A, Tucci, M, Valiviita, J, Vergani, D, 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., Miranda La Hera S., 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., Kummel 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-Crespi 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., Gracia-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., Canas-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., Diaz-Sanchez A., Escartin Vigo J. A., Escoffier S., Ferrero I., Finelli F., Gabarra L., Ganga K., Garcia-Bellido J., Giacomini F., Gozaliasl G., Gwyn S., Hildebrandt H., Huertas-Company M., Jimenez Munoz A., 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., Pontinen M., Reimberg P., Rocci P. -F., Sanchez A. G., Schneider A., Schultheis M., Sefusatti E., Simon P., Spurio Mancini A., Stanford S. A., Steinwagner J., Testera G., Teyssier R., Toft S., Tosi S., Troja A., Tucci M., Valiviita J., and Vergani D.
Abstract: Aims. We derived galaxy colour selections from Euclid and ground-based photometry, aiming to accurately define background galaxy samples in cluster weak-lensing analyses. These selections have been implemented in the Euclid data analysis pipelines for galaxy clusters. Methods. 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. Such colour selections are expressed as a function of the lens redshift. Results. We calibrated galaxy selections using simulated ground-based griz and Euclid YEJEHE photometry. Both selections produce a purity higher than 97%. The griz selection completeness ranges from 30% to 84% in the lens redshift range zl ∈ [0.2, 0.8]. With the full grizYEJEHE selection, the completeness improves by up to 25 percentage points, and the zl range extends up to zl = 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. Furthermore, the calibrated selections provide stable results using alternative photometric aperture definitions obtained from different ground-based telescopes. 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 percentage 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 zl. We show that the calibrated colour selections provide robust results even when observations from a single band are missing from the ground-bas
Published: 2024

99. Euclid preparation: XXXIX. The effect of baryons on the halo mass function

Author: Castro, T, Borgani, S, Costanzi, M, Dakin, J, Dolag, K, Fumagalli, A, Ragagnin, A, Saro, A, Le Brun, A, Aghanim, N, Amara, A, Andreon, S, Auricchio, N, Baldi, M, 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, Congedo, G, Conselice, C, Conversi, L, Copin, Y, Corcione, L, Courbin, F, Courtois, H, Cropper, M, Da Silva, A, Degaudenzi, H, Di Giorgio, A, Dinis, J, Dubath, F, Duncan, C, Dupac, X, Farina, M, Farrens, S, Ferriol, S, Frailis, M, Franceschi, E, Fumana, M, Galeotta, S, Gillis, B, Giocoli, C, Grazian, A, Grupp, F, Haugan, S, Holmes, W, Hormuth, F, Hornstrup, A, Jahnke, K, Keihanen, E, Kermiche, S, Kiessling, A, Kilbinger, M, Kubik, B, Kunz, M, Kurki-Suonio, H, Ligori, S, Lilje, P, Lindholm, V, Lloro, I, Maiorano, E, Mansutti, O, Marggraf, O, Markovic, K, Martinet, N, Marulli, F, Massey, R, Maurogordato, S, Medinaceli, E, Meneghetti, M, Merlin, E, Meylan, G, Moresco, M, Moscardini, L, Munari, E, Niemi, S, Padilla, C, Paltani, S, Pasian, F, Pettorino, V, Pires, S, Polenta, G, Poncet, M, Popa, L, Pozzetti, L, Raison, F, Rebolo, R, Renzi, A, Rhodes, J, Riccio, G, Romelli, E, Roncarelli, M, Saglia, R, Sapone, D, Sartoris, B, Schneider, P, Schrabback, T, Secroun, A, Seidel, G, Serrano, S, Sirignano, C, Sirri, G, Stanco, L, Starck, J, Tallada-Crespi, P, Taylor, A, Tereno, I, Toledo-Moreo, R, Torradeflot, F, Tutusaus, I, Valentijn, E, Valenziano, L, Vassallo, T, Veropalumbo, A, Wang, Y, Weller, J, Zacchei, A, Zamorani, G, Zoubian, J, Zucca, E, Biviano, A, Bozzo, E, Cerna, C, Colodro-Conde, C, Di Ferdinando, D, Mauri, N, Neissner, C, Sakr, Z, Scottez, V, Tenti, M, Viel, M, Wiesmann, M, Akrami, Y, Anselmi, S, Baccigalupi, C, Ballardini, M, Borlaff, A, Bruton, S, Burigana, C, Cabanac, R, Cappi, A, Carvalho, C, Castignani, G, Canas-Herrera, G, Chambers, K, Cooray, A, Coupon, J, Cucciati, O, Diaz-Sanchez, A, Davini, S, De La Torre, S, De Lucia, G, Desprez, G, Di Domizio, S, Dole, H, Escoffier, S, Ferrero, I, Finelli, F, Gabarra, L, Ganga, K, Garcia-Bellido, J, Giacomini, F, Gozaliasl, G, Hildebrandt, H, Ilic, S, Jimanez Munnoz, A, Kajava, J, Kansal, V, Kirkpatrick, C, Legrand, L, Loureiro, A, MacIas-Perez, J, Magliocchetti, M, Mainetti, G, Maoli, R, Martinelli, M, Martins, C, Matthew, S, Maturi, M, Maurin, L, Metcalf, R, Migliaccio, M, Monaco, P, Morgante, G, Nadathur, S, Patrizii, L, Pezzotta, A, Popa, V, Porciani, C, Potter, D, Pontinen, M, Reimberg, P, Rocci, P, Sanchez, A, Schaye, J, Schneider, A, Sefusatti, E, Sereno, M, Simon, P, Spurio Mancini, A, Stadel, J, Stanford, S, Steinwagner, J, Testera, G, Tewes, M, Teyssier, R, Toft, S, Tosi, S, Troja, A, Tucci, M, Valiviita, J, Vergani, D, Castro T., Borgani S., Costanzi M., Dakin J., Dolag K., Fumagalli A., Ragagnin A., Saro A., Le Brun A. M. C., Aghanim N., Amara A., Andreon S., Auricchio N., Baldi M., 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., 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., Dubath F., Duncan C. A. J., Dupac X., Farina M., Farrens S., Ferriol S., Frailis M., Franceschi E., Fumana M., Galeotta S., Gillis B., Giocoli C., Grazian A., Grupp F., Haugan S. V. H., Holmes W., Hormuth F., Hornstrup A., Jahnke K., Keihanen E., 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., 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., 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., Schneider P., Schrabback T., Secroun A., Seidel G., Serrano S., Sirignano C., Sirri G., Stanco L., Starck J. -L., Tallada-Crespi 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., Zacchei A., Zamorani G., Zoubian J., Zucca E., Biviano A., Bozzo E., Cerna C., Colodro-Conde C., Di Ferdinando D., Mauri N., Neissner C., Sakr Z., Scottez V., Tenti M., Viel M., Wiesmann M., Akrami Y., Anselmi S., Baccigalupi C., Ballardini M., Borlaff A. S., Bruton S., Burigana C., Cabanac R., Cappi A., Carvalho C. S., Castignani G., Canas-Herrera G., Chambers K. C., Cooray A. R., Coupon J., Cucciati O., Diaz-Sanchez A., Davini S., De La Torre S., De Lucia G., Desprez G., Di Domizio S., Dole H., Escoffier S., Ferrero I., Finelli F., Gabarra L., Ganga K., Garcia-Bellido J., Giacomini F., Gozaliasl G., Hildebrandt H., Ilic S., Jimanez Munnoz A., 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., Popa V., Porciani C., Potter D., Pontinen M., Reimberg P., Rocci P. -F., Sanchez A. G., Schaye J., Schneider A., Sefusatti E., Sereno M., Simon P., Spurio Mancini A., Stadel J., Stanford S. A., Steinwagner J., Testera G., Tewes M., Teyssier R., Toft S., Tosi S., Troja A., Tucci M., Valiviita J., Vergani D., Castro, T, Borgani, S, Costanzi, M, Dakin, J, Dolag, K, Fumagalli, A, Ragagnin, A, Saro, A, Le Brun, A, Aghanim, N, Amara, A, Andreon, S, Auricchio, N, Baldi, M, 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, Congedo, G, Conselice, C, Conversi, L, Copin, Y, Corcione, L, Courbin, F, Courtois, H, Cropper, M, Da Silva, A, Degaudenzi, H, Di Giorgio, A, Dinis, J, Dubath, F, Duncan, C, Dupac, X, Farina, M, Farrens, S, Ferriol, S, Frailis, M, Franceschi, E, Fumana, M, Galeotta, S, Gillis, B, Giocoli, C, Grazian, A, Grupp, F, Haugan, S, Holmes, W, Hormuth, F, Hornstrup, A, Jahnke, K, Keihanen, E, Kermiche, S, Kiessling, A, Kilbinger, M, Kubik, B, Kunz, M, Kurki-Suonio, H, Ligori, S, Lilje, P, Lindholm, V, Lloro, I, Maiorano, E, Mansutti, O, Marggraf, O, Markovic, K, Martinet, N, Marulli, F, Massey, R, Maurogordato, S, Medinaceli, E, Meneghetti, M, Merlin, E, Meylan, G, Moresco, M, Moscardini, L, Munari, E, Niemi, S, Padilla, C, Paltani, S, Pasian, F, Pettorino, V, Pires, S, Polenta, G, Poncet, M, Popa, L, Pozzetti, L, Raison, F, Rebolo, R, Renzi, A, Rhodes, J, Riccio, G, Romelli, E, Roncarelli, M, Saglia, R, Sapone, D, Sartoris, B, Schneider, P, Schrabback, T, Secroun, A, Seidel, G, Serrano, S, Sirignano, C, Sirri, G, Stanco, L, Starck, J, Tallada-Crespi, P, Taylor, A, Tereno, I, Toledo-Moreo, R, Torradeflot, F, Tutusaus, I, Valentijn, E, Valenziano, L, Vassallo, T, Veropalumbo, A, Wang, Y, Weller, J, Zacchei, A, Zamorani, G, Zoubian, J, Zucca, E, Biviano, A, Bozzo, E, Cerna, C, Colodro-Conde, C, Di Ferdinando, D, Mauri, N, Neissner, C, Sakr, Z, Scottez, V, Tenti, M, Viel, M, Wiesmann, M, Akrami, Y, Anselmi, S, Baccigalupi, C, Ballardini, M, Borlaff, A, Bruton, S, Burigana, C, Cabanac, R, Cappi, A, Carvalho, C, Castignani, G, Canas-Herrera, G, Chambers, K, Cooray, A, Coupon, J, Cucciati, O, Diaz-Sanchez, A, Davini, S, De La Torre, S, De Lucia, G, Desprez, G, Di Domizio, S, Dole, H, Escoffier, S, Ferrero, I, Finelli, F, Gabarra, L, Ganga, K, Garcia-Bellido, J, Giacomini, F, Gozaliasl, G, Hildebrandt, H, Ilic, S, Jimanez Munnoz, A, Kajava, J, Kansal, V, Kirkpatrick, C, Legrand, L, Loureiro, A, MacIas-Perez, J, Magliocchetti, M, Mainetti, G, Maoli, R, Martinelli, M, Martins, C, Matthew, S, Maturi, M, Maurin, L, Metcalf, R, Migliaccio, M, Monaco, P, Morgante, G, Nadathur, S, Patrizii, L, Pezzotta, A, Popa, V, Porciani, C, Potter, D, Pontinen, M, Reimberg, P, Rocci, P, Sanchez, A, Schaye, J, Schneider, A, Sefusatti, E, Sereno, M, Simon, P, Spurio Mancini, A, Stadel, J, Stanford, S, Steinwagner, J, Testera, G, Tewes, M, Teyssier, R, Toft, S, Tosi, S, Troja, A, Tucci, M, Valiviita, J, Vergani, D, Castro T., Borgani S., Costanzi M., Dakin J., Dolag K., Fumagalli A., Ragagnin A., Saro A., Le Brun A. M. C., Aghanim N., Amara A., Andreon S., Auricchio N., Baldi M., 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., 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., Dubath F., Duncan C. A. J., Dupac X., Farina M., Farrens S., Ferriol S., Frailis M., Franceschi E., Fumana M., Galeotta S., Gillis B., Giocoli C., Grazian A., Grupp F., Haugan S. V. H., Holmes W., Hormuth F., Hornstrup A., Jahnke K., Keihanen E., 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., 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., 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., Schneider P., Schrabback T., Secroun A., Seidel G., Serrano S., Sirignano C., Sirri G., Stanco L., Starck J. -L., Tallada-Crespi 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., Zacchei A., Zamorani G., Zoubian J., Zucca E., Biviano A., Bozzo E., Cerna C., Colodro-Conde C., Di Ferdinando D., Mauri N., Neissner C., Sakr Z., Scottez V., Tenti M., Viel M., Wiesmann M., Akrami Y., Anselmi S., Baccigalupi C., Ballardini M., Borlaff A. S., Bruton S., Burigana C., Cabanac R., Cappi A., Carvalho C. S., Castignani G., Canas-Herrera G., Chambers K. C., Cooray A. R., Coupon J., Cucciati O., Diaz-Sanchez A., Davini S., De La Torre S., De Lucia G., Desprez G., Di Domizio S., Dole H., Escoffier S., Ferrero I., Finelli F., Gabarra L., Ganga K., Garcia-Bellido J., Giacomini F., Gozaliasl G., Hildebrandt H., Ilic S., Jimanez Munnoz A., 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., Popa V., Porciani C., Potter D., Pontinen M., Reimberg P., Rocci P. -F., Sanchez A. G., Schaye J., Schneider A., Sefusatti E., Sereno M., Simon P., Spurio Mancini A., Stadel J., Stanford S. A., Steinwagner J., Testera G., Tewes M., Teyssier R., Toft S., Tosi S., Troja A., Tucci M., Valiviita J., and Vergani D.
Abstract: The Euclid photometric survey of galaxy clusters stands as a powerful cosmological tool, with the capacity to significantly propel our understanding of the Universe. Despite being subdominant to dark matter and dark energy, the baryonic component of our Universe holds substantial influence over the structure and mass of galaxy clusters. This paper presents a novel model that can be used to precisely quantify the impact of baryons on the virial halo masses of galaxy clusters using the baryon fraction within a cluster as a proxy for their effect. Constructed on the premise of quasi-adiabaticity, the model includes two parameters, which are calibrated using non-radiative cosmological hydrodynamical simulations, and a single large-scale simulation from the Magneticum set, which includes the physical processes driving galaxy formation. As a main result of our analysis, we demonstrate that this model delivers a remarkable 1% relative accuracy in determining the virial dark matter-only equivalent mass of galaxy clusters starting from the corresponding total cluster mass and baryon fraction measured in hydrodynamical simulations. Furthermore, we demonstrate that this result is robust against changes in cosmological parameters and against variation of the numerical implementation of the subresolution physical processes included in the simulations. Our work substantiates previous claims regarding the impact of baryons on cluster cosmology studies. In particular, we show how neglecting these effects would lead to biased cosmological constraints for a Euclid-like cluster abundance analysis. Importantly, we demonstrate that uncertainties associated with our model arising from baryonic corrections to cluster masses are subdominant when compared to the precision with which mass-observable (i.e. richness) relations will be calibrated using Euclid and to our current understanding of the baryon fraction within galaxy clusters.
Published: 2024

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

Author: 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., and Okumura, K.
Subjects: LARGE scale structure (Astronomy), N-body simulations (Astronomy), SPORTS sciences, STARS, SPECTRAL imaging
Abstract: Context. The European Space Agency's Euclid mission is one of a raft of forthcoming large-scale cosmology surveys that will map the large-scale structure in the Universe with unprecedented precision. The mission will collect a vast amount of data that will be processed and analysed by Euclid's Science Ground Segment (SGS). 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. Aims. In this paper, we present the Euclid SGS simulation framework as it is 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. Methods. Our end-to-end simulation framework started with the production of a large cosmological N-body simulation that we used to construct a realistic galaxy mock catalogue. We performed a selection of galaxies down to IE=26 and 28 mag, respectively, for a Euclid Wide Survey spanning 165 deg2 and a 1 deg2 Euclid Deep Survey. We built realistic stellar density catalogues containing Milky Way-like stars down to H < 26 from a combination of a stellar population synthesis model of the Galaxy and real bright stars. Using the latest instrumental models for both the Euclid instruments and spacecraft as well as Euclid-like observing sequences, we emulated with high fidelity Euclid satellite imaging throughout the mission's lifetime. Results. We present the SC8 dataset, consisting of overlapping visible and near-infrared Euclid Wide Survey and Euclid Deep Survey imaging and low-resolution spectroscopy along with ground-based data in five optical bands. This extensive dataset 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 for future scientific and technical developments and enhancements. [ABSTRACT FROM AUTHOR]
Published: 2024
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