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

Author

Euclid Collaboration, Bisigello, L., Massimo, M., Tortora, C., Fotopoulou, S., Allevato, V., Bolzonella, M., Gruppioni, C., Pozzetti, L., Rodighiero, G., Serjeant, S., Cunha, P. A. C., Gabarra, L., Feltre, A., Humphrey, A., La Franca, F., Landt, H., Mannucci, F., Prandoni, I., Radovich, M., Ricci, F., Salvato, M., Shankar, F., Stern, D., Spinoglio, L., Vergani, D., Vignali, C., Zamorani, G., Yung, L. Y. A., Charlot, S., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Battaglia, P., Bender, R., Bonino, D., Branchini, E., Brau-Nogue, S., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zoubian, J., Zucca, E., Biviano, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Fabbian, G., Graciá-Carpio, J., Marcin, S., Mauri, N., Sakr, Z., Scottez, V., Tenti, M., Akrami, Y., Baccigalupi, C., Ballardini, M., Bethermin, M., Blanchard, A., Borgani, S., Borla, A. S., Bruton, S., Burigana, C., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Coupon, A. R. Cooray J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Ganga, K., García-Bellido, J., Giacomini, F., Gozaliasl, G., Gregorio, A., Hildebrandt, H., Muñoz, A. Jiminez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mainetti, G., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sereno, M., Simon, P., Stadel, J., Stanford, S. A., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Viel, M., and Zinchenko, I. A.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Euclid will cover over 14000 $deg^{2}$ with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our understanding of galaxy evolution and AGN. In this work we identify the best colour selection criteria for AGN, based only on Euclid photometry or including ancillary photometric observations, such as the data that will be available with the Rubin legacy survey of space and time (LSST) and observations already available from Spitzer/IRAC. The analysis is performed for unobscured AGN, obscured AGN, and composite (AGN and star-forming) objects. We make use of the spectro-photometric realisations of infrared-selected targets at all-z (SPRITZ) to create mock catalogues mimicking both the Euclid Wide Survey (EWS) and the Euclid Deep Survey (EDS). Using these catalogues we estimate the best colour selection, maximising the harmonic mean (F1) of completeness and purity. The selection of unobscured AGN in both Euclid surveys is possible with Euclid photometry alone with F1=0.22-0.23, which can increase to F1=0.43-0.38 if we limit at z>0.7. Such selection is improved once the Rubin/LSST filters (a combination of the u, g, r, or z filters) are considered, reaching F1=0.84 and 0.86 for the EDS and EWS, respectively. The combination of a Euclid colour with the [3.6]-[4.5] colour, which is possible only in the EDS, results in an F1-score of 0.59, improving the results using only Euclid filters, but worse than the selection combining Euclid and LSST. The selection of composite ($f_{{\rm AGN}}$=0.05-0.65 at 8-40 $\mu m$) and obscured AGN is challenging, with F1<0.3 even when including ancillary data. This is driven by the similarities between the broad-band spectral energy distribution of these AGN and star-forming galaxies in the wavelength range 0.3-5 $\mu m$., Comment: 25 pages, 28 figures, accepted for publication on A&A

Published
2024

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

Author

Euclid Collaboration, Castander, F. J., Fosalba, P., Stadel, J., Potter, D., Carretero, J., Tallada-Crespí, P., Pozzetti, L., Bolzonella, M., Mamon, G. A., Blot, L., Hoffmann, K., Huertas-Company, M., Monaco, P., Gonzalez, E. J., De Lucia, G., Scarlata, C., Breton, M. -A., Linke, L., Viglione, C., Li, S. -S., Zhai, Z., Baghkhani, Z., Pardede, K., Neissner, C., Teyssier, R., Crocce, M., Tutusaus, I., Miller, L., Congedo, G., Biviano, A., Hirschmann, M., Pezzotta, A., Aussel, H., Hoekstra, H., Kitching, T., Percival, W. J., Guzzo, L., Mellier, Y., Oesch, P. A., Bowler, R. A. A., Bruton, S., Allevato, V., Gonzalez-Perez, V., Manera, M., Avila, S., Kovács, A., Aghanim, N., Altieri, B., Amara, A., Amendola, L., Andreon, S., Auricchio, N., Baldi, M., Balestra, A., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Fourmanoit, N., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Granett, B. R., Grazian, A., Grupp, F., Haugan, S. V. H., Holliman, M. S., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kohley, R., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Laureijs, R., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Masters, D. C., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Mohr, J. J., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Nichol, R. C., Niemi, S. -M., Padilla, C., Paech, K., Paltani, S., Pasian, F., Peacock, J. A., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rosset, C., Rossetti, E., Saglia, R., Sapone, D., Schirmer, M., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tsyganov, A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zerbi, F. M., Zoubian, J., Zucca, E., Baccigalupi, C., Bernardeau, F., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Casenove, P., Castignani, G., Colodro-Conde, C., Di Ferdinando, D., Vigo, J. A. Escartin, Fabbian, G., Finelli, F., Gracia-Carpio, J., Ilić, S., Liebing, P., Marcin, S., Martinelli, M., Matthew, S., Mauri, N., Pöntinen, M., Porciani, C., Sakr, Z., Scottez, V., Sefusatti, E., Steinwagner, J., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Archidiacono, M., Atrio-Barandela, F., Aubourg, E., Balaguera-Antolinez, A., Ballardini, M., Bertacca, D., Bethermin, M., Blanchard, A., Böhringer, H., Borgani, S., Bouvard, T., Cabanac, R., Calabro, A., Quevedo, B. Camacho, Canas-Herrera, G., Cappi, A., Caro, F., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Contini, T., Cooray, A. R., Costanzi, M., Cucciati, O., Davini, S., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Dole, H., Escoffier, S., Ezziati, M., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gasparetto, T., Gaztanaga, E., Giacomini, F., Gianotti, F., Gonzalez, A. H., Gozaliasl, G., Hall, A., Hartley, W. G., Hildebrandt, H., Hjorth, J., Holland, A. D., Ilbert, O., Joudaki, S., Jullo, E., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Graet, J. Le, Legrand, L., Lesgourgues, J., Liaudat, T. I., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Maurin, L., Metcalf, R. B., Migliaccio, M., Miluzio, M., Mora, A., Moretti, C., Morgante, G., Nadathur, S., Nicastro, L., Walton, Nicholas A., Oguri, M., Patrizii, L., Popa, V., Pourtsidou, A., Reimberg, P., Risso, I., Rocci, P. -F., Rollins, R. P., Rusholme, B., Sahlén, M., Sánchez, A. G., Schaye, J., Schewtschenko, J. A., Schneider, A., Schultheis, M., Sereno, M., Shankar, F., Shulevski, A., Silvestri, A., Simon, P., Mancini, A. Spurio, Stanford, S. A., Tanidis, K., Tao, C., Tessore, N., Testera, G., Tewes, M., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Vernizzi, F., Verza, G., Vielzeuf, P., Weaver, J. R., Zalesky, L., Dimauro, P., Duc, P. -A., Fang, Y., Ferguson, A. M. N., Gutierrez, C. M., Kova{č}ić, I., Kruk, S., Brun, A. M. C. Le, Montoro, A., Murray, C., Pagano, L., Paoletti, D., Sarpa, E., Viitanen, A., Martín-Fleitas, J., and Yung, L. Y. A.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present the Flagship galaxy mock, a simulated catalogue of billions of galaxies designed to support the scientific exploitation of the Euclid mission. Euclid is a medium-class mission of the European Space Agency optimised to determine the properties of dark matter and dark energy on the largest scales of the Universe. It probes structure formation over more than 10 billion years primarily from the combination of weak gravitational lensing and galaxy clustering data. The breath of Euclid's data will also foster a wide variety of scientific analyses. The Flagship simulation was developed to provide a realistic approximation to the galaxies that will be observed by Euclid and used in its scientific analyses. We ran a state-of-the-art N-body simulation with four trillion particles, producing a lightcone on the fly. From the dark matter particles, we produced a catalogue of 16 billion haloes in one octant of the sky in the lightcone up to redshift z=3. We then populated these haloes with mock galaxies using a halo occupation distribution and abundance matching approach, calibrating the free parameters of the galaxy mock against observed correlations and other basic galaxy properties. Modelled galaxy properties include luminosity and flux in several bands, redshifts, positions and velocities, spectral energy distributions, shapes and sizes, stellar masses, star formation rates, metallicities, emission line fluxes, and lensing properties. We selected a final sample of 3.4 billion galaxies with a magnitude cut of H_E<26, where we are complete. We have performed a comprehensive set of validation tests to check the similarity to observational data and theoretical models. In particular, our catalogue is able to closely reproduce the main characteristics of the weak lensing and galaxy clustering samples to be used in the mission's main cosmological analysis. (abridged), Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

Published
2024

3. Euclid. I. Overview of the Euclid mission

Author

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

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

Published
2024

4. Euclid. II. The VIS Instrument

Author

Euclid Collaboration, Cropper, M., Al-Bahlawan, A., Amiaux, J., Awan, S., Azzollini, R., Benson, K., Berthe, M., Boucher, J., Bozzo, E., Brockley-Blatt, C., Candini, G. P., Cara, C., Chaudery, R. A., Cole, R. E., Danto, P., Denniston, J., Di Giorgio, A. M., Dryer, B., Endicott, J., Dubois, J. -P., Farina, M., Galli, E., Genolet, L., Gow, J. P. D., Guttridge, P., Hailey, M., Hall, D., Harper, C., Holland, A. D., Horeau, B., Hu, D., King, R., James, R. E., Larcheveque, C., Khalil, A., Lawrenson, A., Liebing, P., Martignac, J., McCracken, H. J., Murray, N., Nakajima, R., Niemi, S. -M., Pendem, A., Paltani, S., Philippon, A., Pool, P., Plana, C., Pottinger, S., Racca, G. D., Rousseau, A., Ruane, K., Salatti, M., Salvignol, J. -C., Sciortino, A., Short, Alexander, Liu, S. J., Skottfelt, J., Swindells, I., Smit, S. J. A., Szafraniec, M., Thomas, P. D., Thomas, W., Tommasi, E., Winter, B., Tosti, S., Visticot, F., Walton, D. M., Willis, G., Mora, A., Kohley, R., Massey, R., Nightingale, J. W., Kitching, T., Hoekstra, H., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Aussel, H., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Bender, R., Bodendorf, C., Boenke, T., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, R., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cuby, J. -G., Cuillandre, J. -C., Da Silva, A., Degaudenzi, H., Dinis, J., Dolding, C., Douspis, M., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Fabricius, M., Farrens, S., Ferriol, S., Fosalba, P., Fotopoulou, S., Frailis, M., Franceschi, E., Franzetti, P., Frugier, P. -A., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Herent, O., Hoar, J., Holliman, M. S., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kilbinger, M., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Alvarez, J. Lorenzo, Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Martinet, N., Marulli, F., Masters, D. C., Maurogordato, S., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Miller, L., Mohr, J. J., Moresco, M., Moscardini, L., Nichol, R. C., Nutma, T., Padilla, C., Paech, K., Pasian, F., Peacock, J. A., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Refregier, A., Renzi, A., Riccio, G., Rix, Hans-Walter, Romelli, E., Roncarelli, M., Rosset, C., Rossetti, E., Rottgering, H. J. A., Saglia, R., Sapone, D., Sauvage, M., Scaramella, R., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wachter, S., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Baccigalupi, C., Bernardeau, F., Biviano, A., Bolzonella, M., Boucaud, A., Burigana, C., Calabrese, M., Casenove, P., Colodro-Conde, C., Crocce, M., De Lucia, G., Di Ferdinando, D., Vigo, J. A. Escartin, Fabbian, G., Farinelli, R., Finelli, F., George, K., Gracia-Carpio, J., Ilić, S., Israel, H., Mainetti, G., Marcin, S., Martinelli, M., Mauri, N., Neissner, C., Nguyen-Kim, H. N., Pezzotta, A., Pöntinen, M., Porciani, C., Sakr, Z., Scottez, V., Sefusatti, E., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Aubourg, E., Ballardini, M., Bertacca, D., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Calabro, A., Calderone, G., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Chary, R., Contarini, S., Cooray, A. R., Cordes, O., Costanzi, M., Cucciati, O., Davini, S., De Caro, B., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Gregorio, A., Hall, A., Hartley, W. G., Hildebrandt, H., Hjorth, J., Huertas-Company, M., Ilbert, O., Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Lacasa, F., Graet, J. Le, Legrand, L., Libet, G., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., McPartland, C. J. R., Metcalf, R. B., Migliaccio, M., Miluzio, M., Monaco, P., Moretti, C., Morgante, G., Nadathur, S., Walton, Nicholas A., Odier, J., Oguri, M., Patrizii, L., Popa, V., Potter, D., Pourtsidou, A., Reimberg, P., Risso, I., Rocci, P. -F., Rollins, R. P., Rusholme, B., Sahlén, M., Sánchez, A. G., Scarlata, C., Schaye, J., Schewtschenko, J. A., Schneider, A., Schultheis, M., Sereno, M., Shankar, F., Sikkema, G., Silvestri, A., Simon, P., Mancini, A. Spurio, Stadel, J., Stanford, S. A., Steinwagner, J., Tanidis, K., Tao, C., Tessore, N., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Vernizzi, F., Verza, G., Vielzeuf, P., Weaver, J. R., Zalesky, L., Zinchenko, I. A., Archidiacono, M., Atrio-Barandela, F., Bouvard, T., Caro, F., Dimauro, P., Duc, P. -A., Fang, Y., Ferguson, A. M. N., Gasparetto, T., Gutierrez, C. M., Kova{č}ić, I., Kruk, S., Brun, A. M. C. Le, Liaudat, T. I., Montoro, A., Murray, C., Pagano, L., Paoletti, D., Sarpa, E., Viitanen, A., Lesgourgues, J., and Martín-Fleitas, J.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

This paper presents the specification, design, and development of the Visible Camera (VIS) on the ESA Euclid mission. VIS is a large optical-band imager with a field of view of 0.54 deg^2 sampled at 0.1" with an array of 609 Megapixels and spatial resolution of 0.18". It will be used to survey approximately 14,000 deg^2 of extragalactic sky to measure the distortion of galaxies in the redshift range z=0.1-1.5 resulting from weak gravitational lensing, one of the two principal cosmology probes of Euclid. With photometric redshifts, the distribution of dark matter can be mapped in three dimensions, and, from how this has changed with look-back time, the nature of dark energy and theories of gravity can be constrained. The entire VIS focal plane will be transmitted to provide the largest images of the Universe from space to date, reaching m_AB>24.5 with S/N >10 in a single broad I_E~(r+i+z) band over a six year survey. The particularly challenging aspects of the instrument are the control and calibration of observational biases, which lead to stringent performance requirements and calibration regimes. With its combination of spatial resolution, calibration knowledge, depth, and area covering most of the extra-Galactic sky, VIS will also provide a legacy data set for many other fields. This paper discusses the rationale behind the VIS concept and describes the instrument design and development before reporting the pre-launch performance derived from ground calibrations and brief results from the in-orbit commissioning. VIS should reach fainter than m_AB=25 with S/N>10 for galaxies of full-width half-maximum of 0.3" in a 1.3" diameter aperture over the Wide Survey, and m_AB>26.4 for a Deep Survey that will cover more than 50 deg^2. The paper also describes how VIS works with the other Euclid components of survey, telescope, and science data processing to extract the cosmological information., Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

Published
2024

5. Euclid preparation. Sensitivity to neutrino parameters

Author

Euclid Collaboration, Archidiacono, M., Lesgourgues, J., Casas, S., Pamuk, S., Schöneberg, N., Sakr, Z., Parimbelli, G., Schneider, A., Peters, F. Hervas, Pace, F., Sabarish, V. M., Costanzi, M., Camera, S., Carbone, C., Clesse, S., Frusciante, N., Fumagalli, A., Monaco, P., Scott, D., Viel, M., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Cardone, V. F., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sapone, D., Sartoris, B., Scaramella, R., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Colodro-Conde, C., Crocce, M., Fabbian, G., Graciá-Carpio, J., Mainetti, G., Martinelli, M., Mauri, N., Neissner, C., Scottez, V., Tenti, M., Wiesmann, M., Akrami, Y., Anselmi, S., Baccigalupi, C., Ballardini, M., Bernardeau, F., Bertacca, D., Borgani, S., Borsato, E., Bruton, S., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Contarini, S., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Di Domizio, S., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferreira, P. G., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Gregorio, A., Hall, A., Hildebrandt, H., Ilić, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Morgante, G., Nadathur, S., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Sánchez, A. G., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., and Vielzeuf, P.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The Euclid mission of the European Space Agency will deliver weak gravitational lensing and galaxy clustering surveys that can be used to constrain the standard cosmological model and extensions thereof. We present forecasts from the combination of these surveys on the sensitivity to cosmological parameters including the summed neutrino mass $M_\nu$ and the effective number of relativistic species $N_{\rm eff}$ in the standard $\Lambda$CDM scenario and in a scenario with dynamical dark energy ($w_0 w_a$CDM). We compare the accuracy of different algorithms predicting the nonlinear matter power spectrum for such models. We then validate several pipelines for Fisher matrix and MCMC forecasts, using different theory codes, algorithms for numerical derivatives, and assumptions concerning the non-linear cut-off scale. The Euclid primary probes alone will reach a sensitivity of $\sigma(M_\nu)=$56meV in the $\Lambda$CDM+$M_\nu$ model, whereas the combination with CMB data from Planck is expected to achieve $\sigma(M_\nu)=$23meV and raise the evidence for a non-zero neutrino mass to at least the $2.6\sigma$ level. This can be pushed to a $4\sigma$ detection if future CMB data from LiteBIRD and CMB Stage-IV are included. In combination with Planck, Euclid will also deliver tight constraints on $\Delta N_{\rm eff}< 0.144$ (95%CL) in the $\Lambda$CDM+$M_\nu$+$N_{\rm eff}$ model, or $\Delta N_{\rm eff}< 0.063$ when future CMB data are included. When floating $(w_0, w_a)$, we find that the sensitivity to $N_{\rm eff}$ remains stable, while that to $M_\nu$ degrades at most by a factor 2. This work illustrates the complementarity between the Euclid spectroscopic and imaging/photometric surveys and between Euclid and CMB constraints. Euclid will have a great potential for measuring the neutrino mass and excluding well-motivated scenarios with additional relativistic particles., Comment: 48 pages, 33 figures

Published
2024

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

Author

Euclid Collaboration, Congedo, G., Miller, L., Taylor, A. N., Cross, N., Duncan, C. A. J., Kitching, T., Martinet, N., Matthew, S., Schrabback, T., Tewes, M., Welikala, N., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holliman, M. S., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Morin, B., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Tavagnacco, D., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Guinet, D., Hall, A., Hildebrandt, H., Ilić, S., Muñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Macias-Perez, J., Maggio, G., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Peel, A., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schewtschenko, J. A., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., and Vergani, D.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Physics - Data Analysis, Statistics and Probability, Statistics - Computation
Abstract

LensMC is a weak lensing shear measurement method developed for Euclid and Stage-IV surveys. It is based on forward modelling in order to deal with convolution by a point spread function (PSF) with comparable size to many galaxies; sampling the posterior distribution of galaxy parameters via Markov Chain Monte Carlo; and marginalisation over nuisance parameters for each of the 1.5 billion galaxies observed by Euclid. We quantified the scientific performance through high-fidelity images based on the Euclid Flagship simulations and emulation of the Euclid VIS images; realistic clustering with a mean surface number density of 250 arcmin$^{-2}$ ($I_{\rm E}<29.5$) for galaxies, and 6 arcmin$^{-2}$ ($I_{\rm E}<26$) for stars; and a diffraction-limited chromatic PSF with a full width at half maximum of $0.^{\!\prime\prime}2$ and spatial variation across the field of view. LensMC measured objects with a density of 90 arcmin$^{-2}$ ($I_{\rm E}<26.5$) in 4500 deg$^2$. The total shear bias was broken down into measurement (our main focus here) and selection effects (which will be addressed elsewhere). We found measurement multiplicative and additive biases of $m_1=(-3.6\pm0.2)\times10^{-3}$, $m_2=(-4.3\pm0.2)\times10^{-3}$, $c_1=(-1.78\pm0.03)\times10^{-4}$, $c_2=(0.09\pm0.03)\times10^{-4}$; a large detection bias with a multiplicative component of $1.2\times10^{-2}$ and an additive component of $-3\times10^{-4}$; and a measurement PSF leakage of $\alpha_1=(-9\pm3)\times10^{-4}$ and $\alpha_2=(2\pm3)\times10^{-4}$. When model bias is suppressed, the obtained measurement biases are close to Euclid requirement and largely dominated by undetected faint galaxies ($-5\times10^{-3}$). Although significant, model bias will be straightforward to calibrate given the weak sensitivity. LensMC is publicly available at https://gitlab.com/gcongedo/LensMC, Comment: Appearing on A&A. 28 pages, 18 figures, and 2 tables

Published
2024
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7. Euclid preparation. XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning

Author

Euclid Collaboration, Aussel, B., Kruk, S., Walmsley, M., Huertas-Company, M., Castellano, M., Conselice, C. J., Veneri, M. Delli, Sánchez, H. Domínguez, Duc, P. -A., Kuchner, U., La Marca, A., Margalef-Bentabol, B., Marleau, F. R., Stevens, G., Toba, Y., Tortora, C., Wang, L., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mainetti, G., Marcin, S., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Borgani, S., Borlaff, A. S., Bretonnière, H., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Coupon, J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., George, K., Giacomini, F., Gozaliasl, G., Gregorio, A., Guinet, D., Hall, A., Hildebrandt, H., Munoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Walton, Nicholas A., Peel, A., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Stanford, S. A., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., and Zinchenko, I. A.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in Euclid using Zoobot a convolutional neural network pretrained with 450000 galaxies from the Galaxy Zoo project. We adapted Zoobot for emulated Euclid images, generated based on Hubble Space Telescope COSMOS images, and with labels provided by volunteers in the Galaxy Zoo: Hubble project. We demonstrate that the trained Zoobot model successfully measures detailed morphology for emulated Euclid images. It effectively predicts whether a galaxy has features and identifies and characterises various features such as spiral arms, clumps, bars, disks, and central bulges. When compared to volunteer classifications Zoobot achieves mean vote fraction deviations of less than 12% and an accuracy above 91% for the confident volunteer classifications across most morphology types. However, the performance varies depending on the specific morphological class. For the global classes such as disk or smooth galaxies, the mean deviations are less than 10%, with only 1000 training galaxies necessary to reach this performance. For more detailed structures and complex tasks like detecting and counting spiral arms or clumps, the deviations are slightly higher, around 12% with 60000 galaxies used for training. In order to enhance the performance on complex morphologies, we anticipate that a larger pool of labelled galaxies is needed, which could be obtained using crowdsourcing. Finally, our findings imply that the model can be effectively adapted to new morphological labels. We demonstrate this adaptability by applying Zoobot to peculiar galaxies. In summary, our trained Zoobot CNN can readily predict morphological catalogues for Euclid images., Comment: 27 pages, 26 figures, 5 tables, published in A&A

Published
2024
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8. Euclid preparation. Optical emission-line predictions of intermediate-z galaxy populations in GAEA for the Euclid Deep and Wide Surveys

Author

Euclid Collaboration, Scharré, L., Hirschmann, M., De Lucia, G., Charlot, S., Fontanot, F., Spinelli, M., Xie, L., Feltre, A., Allevato, V., Plat, A., Bremer, M. N., Fotopoulou, S., Gabarra, L., Granett, B. R., Moresco, M., Scarlata, C., Pozzetti, L., Spinoglio, L., Talia, M., Zamorani, G., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kitching, T., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mainetti, G., Martinelli, M., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Anselmi, S., Baccigalupi, C., Ballardini, M., Bethermin, M., Blanchard, A., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Calabro, A., Cañas-Herrera, G., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Contarini, S., Contini, T., Cooray, A. R., Coupon, J., Cucciati, O., Desprez, G., Di Domizio, S., Dole, H., ánchez, A. Díaz-S, Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Ganga, K., García-Bellido, J., Gaztanaga, E., George, K., Giacomini, F., Gozaliasl, G., Gregorio, A., Hall, A., Hildebrandt, H., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Walton, Nicholas A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Sánchez, A. G., Schneider, A., Schultheis, M., Sereno, M., Simon, P., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Vergani, D., Verza, G., and Zinchenko, I. A.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

In anticipation of the Euclid Wide and Deep Surveys, we present optical emission-line predictions at intermediate redshifts from 0.4 to 2.5. Our approach combines a mock light cone from the GAEA semi-analytic model to self-consistently model nebular emission from HII regions, narrow-line regions of active galactic nuclei (AGN), and evolved stellar populations. Our analysis focuses on seven optical emission lines: H$\alpha$, H$\beta$, [SII]$\lambda\lambda 6717, 6731$, [NII]$\lambda 6584$, [OI]$\lambda 6300$, [OIII]$\lambda 5007$, and [OII]$\lambda\lambda 3727, 3729$. We find that Euclid will predominantly observe massive, star-forming, and metal-rich line-emitters. Interstellar dust, modelled using a Calzetti law with mass-dependent scaling, may decrease observable percentages by a further 20-30% with respect to our underlying emission-line populations from GAEA. We predict Euclid to observe around 30-70% of H$\alpha$-, [NII]-, [SII]-, and [OIII]-emitting galaxies at redshift below 1 and under 10% at higher redshift. Observability of H$\beta$-, [OII]-, and [OI]- emission is limited to below 5%. For the Euclid-observable sample, we find that BPT diagrams can effectively distinguish between different galaxy types up to around redshift 1.8, attributed to the bias toward metal-rich systems. Moreover, we show that the relationships of H$\alpha$ and [OIII]+H$\beta$ to the star-formation rate, and the [OIII]-AGN luminosity relation, exhibit minimal changes with increasing redshift. Based on line ratios [NII]/H$\alpha$, [NII]/[OII], and [NII]/[SII], we further propose novel z-invariant tracers for the black hole accretion rate-to-star formation rate ratio. Lastly, we find that commonly used metallicity estimators display gradual shifts in normalisations with increasing redshift, while maintaining the overall shape of local calibrations. This is in tentative agreement with recent JWST data., Comment: 32 pages, 15 figures, submitted to A&A

Published
2024
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9. Euclid preparation: XLVIII. The pre-launch Science Ground Segment simulation framework

Author

Euclid Collaboration, Serrano, S., Hudelot, P., Seidel, G., Pollack, J. E., Jullo, E., Torradeflot, F., Benielli, D., Fahed, R., Auphan, T., Carretero, J., Aussel, H., Casenove, P., Castander, F. J., Davies, J. E., Fourmanoit, N., Huot, S., Kara, A., Keihänen, E., Kermiche, S., Okumura, K., Zoubian, J., Ealet, A., Boucaud, A., Bretonnière, H., Casas, R., Clément, B., Duncan, C. A. J., George, K., Kiiveri, K., Kurki-Suonio, H., Kümmel, M., Laugier, D., Mainetti, G., Mohr, J. J., Montoro, A., Neissner, C., Rosset, C., Schirmer, M., Tallada-Crespí, P., Tonello, N., Venhola, A., Verderi, A., Zacchei, A., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Azzollini, R., Baccigalupi, C., Baldi, M., Bardelli, S., Basset, A., Battaglia, P., Bernardeau, F., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Cledassou, R., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Crocce, M., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Kiessling, A., Kitching, T., Kohley, R., Kunz, M., Boulc'h, Q. Le, Liebing, P., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Morris, P., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. -M., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Rusholme, B., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Sauvage, M., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. -L., Steinwagner, J., Taylor, A. N, Teplitz, H., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bozzo, E., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mauri, N., Scottez, V., Tenti, M., Akrami, Y., Allevato, V., Ballardini, M., Blanchard, A., Borgani, S., Borlaff, A. S., Bruton, S., Burigana, C., Cappi, A., Carvalho, C. S., Castro, T., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., Desai, S., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Gregorio, A., Hildebrandt, H., Huertas-Company, M., Ilbert, O., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Schneider, A., Sereno, M., Shulevski, A., Simon, P., Mancini, A. Spurio, Stadel, J., Tewes, M., Teyssier, R., Toft, S., Tucci, M., Valiviita, J., Viel, M., and Zinchenko, I. A.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The European Space Agency's Euclid mission is one of the upcoming generation of large-scale cosmology surveys, which will map the large-scale structure in the Universe with unprecedented precision. The development and validation of the SGS pipeline requires state-of-the-art simulations with a high level of complexity and accuracy that include subtle instrumental features not accounted for previously as well as faster algorithms for the large-scale production of the expected Euclid data products. In this paper, we present the Euclid SGS simulation framework as applied in a large-scale end-to-end simulation exercise named Science Challenge 8. Our simulation pipeline enables the swift production of detailed image simulations for the construction and validation of the Euclid mission during its qualification phase and will serve as a reference throughout operations. Our end-to-end simulation framework starts with the production of a large cosmological N-body & mock galaxy catalogue simulation. We perform a selection of galaxies down to I_E=26 and 28 mag, respectively, for a Euclid Wide Survey spanning 165 deg^2 and a 1 deg^2 Euclid Deep Survey. We build realistic stellar density catalogues containing Milky Way-like stars down to H<26. Using the latest instrumental models for both the Euclid instruments and spacecraft as well as Euclid-like observing sequences, we emulate with high fidelity Euclid satellite imaging throughout the mission's lifetime. We present the SC8 data set consisting of overlapping visible and near-infrared Euclid Wide Survey and Euclid Deep Survey imaging and low-resolution spectroscopy along with ground-based. This extensive data set enables end-to-end testing of the entire ground segment data reduction and science analysis pipeline as well as the Euclid mission infrastructure, paving the way to future scientific and technical developments and enhancements., Comment: 39 pages, 25 figures, A&A submitted

Published
2024
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10. Euclid Preparation. TBD. Impact of magnification on spectroscopic galaxy clustering

Author

Euclid Collaboration, Jelic-Cizmek, G., Sorrenti, F., Lepori, F., Bonvin, C., Camera, S., Castander, F. J., Durrer, R., Fosalba, P., Kunz, M., Lombriser, L., Tutusaus, I., Viglione, C., Sakr, Z., Aghanim, N., Amara, A., Andreon, S., Baldi, M., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Cropper, M., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kurki-Suonio, H., Lilje, P. B., Lindholm, V., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Meneghetti, M., Merlin, E., Meylan, G., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Surace, C., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Boucaud, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Liebing, P., Mauri, N., Neissner, C., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Bruton, S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., {n}as-Herrera, G. Ca\, Chambers, K. C., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferreira, P. G., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Giacomini, F., Gozaliasl, G., Guinet, D., Hildebrandt, H., Ilić, S., {n}oz, A. Jimenez Mu\, Joudaki, S., Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Magliocchetti, M., Mainetti, G., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Schultheis, M., Sefusatti, E., Sereno, M., Silvestri, A., Simon, P., Mancini, A. Spurio, Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Vergani, D., and Tanidis, K.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

In this paper we investigate the impact of lensing magnification on the analysis of Euclid's spectroscopic survey, using the multipoles of the 2-point correlation function for galaxy clustering. We determine the impact of lensing magnification on cosmological constraints, and the expected shift in the best-fit parameters if magnification is ignored. We consider two cosmological analyses: i) a full-shape analysis based on the $\Lambda$CDM model and its extension $w_0w_a$CDM and ii) a model-independent analysis that measures the growth rate of structure in each redshift bin. We adopt two complementary approaches in our forecast: the Fisher matrix formalism and the Markov chain Monte Carlo method. The fiducial values of the local count slope (or magnification bias), which regulates the amplitude of the lensing magnification, have been estimated from the Euclid Flagship simulations. We use linear perturbation theory and model the 2-point correlation function with the public code coffe. For a $\Lambda$CDM model, we find that the estimation of cosmological parameters is biased at the level of 0.4-0.7 standard deviations, while for a $w_0w_a$CDM dynamical dark energy model, lensing magnification has a somewhat smaller impact, with shifts below 0.5 standard deviations. In a model-independent analysis aiming to measure the growth rate of structure, we find that the estimation of the growth rate is biased by up to $1.2$ standard deviations in the highest redshift bin. As a result, lensing magnification cannot be neglected in the spectroscopic survey, especially if we want to determine the growth factor, one of the most promising ways to test general relativity with Euclid. We also find that, by including lensing magnification with a simple template, this shift can be almost entirely eliminated with minimal computational overhead., Comment: 23 pages, 14 figures

Published
2023

11. Euclid preparation. XXXIX. The effect of baryons on the Halo Mass Function

Author

Euclid Collaboration, Castro, T., Borgani, S., Costanzi, M., Dakin, J., Dolag, K., Fumagalli, A., Ragagnin, A., Saro, A., Brun, A. M. C. Le, 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., Keihänen, 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-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., 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., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Cucciati, O., Díaz-Sánchez, 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., Ilić, S., Munñoz, A. Jimanez, 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., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schaye, J., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, 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.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
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 sub-dominant to dark matter and dark energy, the baryonic component in our Universe holds substantial influence over the structure and mass of galaxy clusters. This paper presents a novel model to precisely quantify the impact of baryons on galaxy cluster virial halo masses, using the baryon fraction within a cluster as proxy for their effect. Constructed on the premise of quasi-adiabaticity, the model includes two parameters 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 one percent 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 varying the numerical implementation of the sub-resolution physical processes included in the simulations. Our work substantiates previous claims about 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 sub-dominant when compared to the precision with which mass-observable relations will be calibrated using Euclid, as well as our current understanding of the baryon fraction within galaxy clusters., Comment: 18 pages, 10 figures, 4 tables, 1 appendix, abstract abridged for arXiv submission; v2 matches published version

Published
2023

13. 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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15. COSMOGRAIL XIX: Time delays in 18 strongly lensed quasars from 15 years of optical monitoring

Author

Millon, M., Courbin, F., Bonvin, V., Paic, E., Meylan, G., Tewes, M., Sluse, D., Magain, P., Chan, J. H. H., Galan, A., Joseph, R., Lemon, C., Tihhonova, O., Anderson, R. I., Marmier, M., Chazelas, B., Lendl, M., Triaud, A. H. M. J., and Wyttenbach, A.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present the results of 15 years of monitoring lensed quasars, which was conducted by the COSMOGRAIL programme at the Leonhard Euler 1.2m Swiss Telescope. The decade-long light curves of 23 lensed systems are presented for the first time. We complement our data set with other monitoring data available in the literature to measure the time delays in 18 systems, among which nine reach a relative precision better than 15% for at least one time delay. To achieve this, we developed an automated version of the curve-shifting toolbox PyCS to ensure robust estimation of the time delay in the presence of microlensing, while accounting for the errors due to the imperfect representation of microlensing. We also re-analysed the previously published time delays of RX J1131$-$1231 and HE 0435$-$1223, by adding six and two new seasons of monitoring, respectively, and confirming the previous time-delay measurements. When the time delay measurement is possible, we corrected the light curves of the lensed images from their time delay and present the difference curves to highlight the microlensing signal contained in the data. To date, this is the largest sample of decade-long lens monitoring data, which is useful to measure $H_0$ and the size of quasar accretion discs with microlensing as well as to study quasar variability., Comment: Published in A&A, 31 pages, 8 figures, 3 Tables

Published
2020
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16. COSMOGRAIL XVIII: time delays of the quadruply lensed quasar WFI2033-4723

Author

Bonvin, V., Millon, M., Chan, J. H. H., Courbin, F., Rusu, C. E., Sluse, D., Suyu, S. H., Wong, K. C., Fassnacht, C. D., Marshall, P. J., Treu, T., Buckley-Geer, E., Frieman, J., Hempel, A., Kim, S., Lachaume, R., Rabus, M., Chao, D. C. -Y., Chijani, M., Gilman, D., Gilmore, K., Rojas, K., Williams, P., Anguita, T., Kochanek, C. S., Meylan, G., Morgan, C., Motta, V., and Tewes, M.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present new measurements of the time delays of WFI2033-4723. The data sets used in this work include 14 years of data taken at the 1.2m Leonhard Euler Swiss telescope, 13 years of data from the SMARTS 1.3m telescope at Las Campanas Observatory and a single year of high-cadence and high-precision monitoring at the MPIA 2.2m telescope. The time delays measured from these different data sets, all taken in the R-band, are in good agreement with each other and with previous measurements from the literature. Combining all the time-delay estimates from our data sets results in Dt_AB = 36.2-0.8+0.7 days (2.1% precision), Dt_AC = -23.3-1.4+1.2 days (5.6%) and Dt_BC = -59.4-1.3+1.3 days (2.2%). In addition, the close image pair A1-A2 of the lensed quasars can be resolved in the MPIA 2.2m data. We measure a time delay consistent with zero in this pair of images. We also explore the prior distributions of microlensing time-delay potentially affecting the cosmological time-delay measurements of WFI2033-4723. There is however no strong indication in our measurements that microlensing time delay is neither present nor absent. This work is part of a H0LiCOW series focusing on measuring the Hubble constant from WFI2033-4723., Comment: Submitted to Astronomy and Astrophysics

Published
2019
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17. The fourth data release of the Kilo-Degree Survey: ugri imaging and nine-band optical-IR photometry over 1000 square degrees

Author

Kuijken, K., Heymans, C., Dvornik, A., Hildebrandt, H., de Jong, J. T. A., Wright, A. H., Erben, T., Bilicki, M., Giblin, B., Shan, H. -Y., Getman, F., Grado, A., Hoekstra, H., Miller, L., Napolitano, N., Paolilo, M., Radovich, M., Schneider, P., Sutherland, W., Tewes, M., Tortora, C., Valentijn, E. A., and Kleijn, G. A. Verdoes

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The Kilo-Degree Survey (KiDS) is an ongoing optical wide-field imaging survey with the OmegaCAM camera at the VLT Survey Telescope, specifically designed for measuring weak gravitational lensing by galaxies and large-scale structure. When completed it will consist of 1350 square degrees imaged in four filters (ugri). Here we present the fourth public data release which more than doubles the area of sky covered by data release 3. We also include aperture-matched ZYJHKs photometry from our partner VIKING survey on the VISTA telescope in the photometry catalogue. We illustrate the data quality and describe the catalogue content. Two dedicated pipelines are used for the production of the optical data. The Astro-WISE information system is used for the production of co-added images in the four survey bands, while a separate reduction of the r-band images using the theli pipeline is used to provide a source catalogue suitable for the core weak lensing science case. All data have been re-reduced for this data release using the latest versions of the pipelines. The VIKING photometry is obtained as forced photometry on the theli sources, using a re-reduction of the VIKING data that starts from the VISTA pawprints. Modifications to the pipelines with respect to earlier releases are described in detail. The photometry is calibrated to the Gaia DR2 G band using stellar locus regression. In this data release a total of 1006 square-degree survey tiles with stacked ugri images are made available, accompanied by weight maps, masks, and single-band source lists. We also provide a multi-band catalogue based on r-band detections, including homogenized photometry and photometric redshifts, for the whole dataset. Mean limiting magnitudes (5 sigma in a 2" aperture) are 24.23, 25.12, 25.02, 23.68 in ugri, respectively, and the mean r-band seeing is 0.70"., Comment: 25 pages, accepted for publication in Astronomy and Astrophysics. For access to the images and catalogues see http://kids.strw.leidenuniv.nl/DR4/

Published
2019
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18. Euclid Preparation IV. Impact of undetected galaxies on weak-lensing shear measurements

Author

Euclid Collaboration, Martinet, N., Schrabback, T., Hoekstra, H., Tewes, M., Herbonnet, R., Schneider, P., Hernandez-Martin, B., Taylor, A. N., Brinchmann, J., Carvalho, C. S., Castellano, M., Congedo, G., Gillis, B. R., Jullo, E., Kümmel, M., Ligori, S., Lilje, P. B., Padilla, C., Paris, D., Peacock, J. A., Pilo, S., Pujol, A., Scott, D., and Toledo-Moreo, R.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

In modern weak-lensing surveys, the common approach to correct for residual systematic biases in the shear is to calibrate shape measurement algorithms using simulations. These simulations must fully capture the complexity of the observations to avoid introducing any additional bias. In this paper we study the importance of faint galaxies below the observational detection limit of a survey. We simulate simplified Euclid VIS images including and excluding this faint population, and measure the shift in the multiplicative shear bias between the two sets of simulations. We measure the shear with three different algorithms: a moment-based approach, model fitting, and machine learning. We find that for all methods, a spatially uniform random distribution of faint galaxies introduces a shear multiplicative bias of the order of a few times $10^{-3}$. This value increases to the order of $10^{-2}$ when including the clustering of the faint galaxies, as measured in the Hubble Space Telescope Ultra-Deep Field. The magnification of the faint background galaxies due to the brighter galaxies along the line of sight is found to have a negligible impact on the multiplicative bias. We conclude that the undetected galaxies must be included in the calibration simulations with proper clustering properties down to magnitude 28 in order to reach a residual uncertainty on the multiplicative shear bias calibration of a few times $10^{-4}$, in line with the $2\times10^{-3}$ total accuracy budget required by the scientific objectives of the Euclid survey. We propose two complementary methods for including faint galaxy clustering in the calibration simulations., Comment: Version published in A&A

Published
2019
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19. 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

20. KiDS+VIKING-450: Cosmic shear tomography with optical+infrared data

Author

Hildebrandt, H., Köhlinger, F., Busch, J. L. van den, Joachimi, B., Heymans, C., Kannawadi, A., Wright, A. H., Asgari, M., Blake, C., Hoekstra, H., Joudaki, S., Kuijken, K., Miller, L., Morrison, C. B., Tröster, T., Amon, A., Archidiacono, M., Brieden, S., Choi, A., de Jong, J. T. A., Erben, T., Giblin, B., Mead, A., Peacock, J. A., Radovich, M., Schneider, P., Sifón, C., and Tewes, M.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present a tomographic cosmic shear analysis of the Kilo-Degree Survey (KiDS) combined with the VISTA Kilo-Degree Infrared Galaxy Survey (VIKING). This is the first time that a full optical to near-infrared data set has been used for a wide-field cosmological weak lensing experiment. This unprecedented data, spanning $450~$deg$^2$, allows us to improve significantly the estimation of photometric redshifts, such that we are able to include robustly higher-redshift sources for the lensing measurement, and - most importantly - solidify our knowledge of the redshift distributions of the sources. Based on a flat $\Lambda$CDM model we find $S_8\equiv\sigma_8\sqrt{\Omega_{\rm m}/0.3}=0.737_{-0.036}^{+0.040}$ in a blind analysis from cosmic shear alone. The tension between KiDS cosmic shear and the Planck-Legacy CMB measurements remains in this systematically more robust analysis, with $S_8$ differing by $2.3\sigma$. This result is insensitive to changes in the priors on nuisance parameters for intrinsic alignment, baryon feedback, and neutrino mass. KiDS shear measurements are calibrated with a new, more realistic set of image simulations and no significant B-modes are detected in the survey, indicating that systematic errors are under control. When calibrating our redshift distributions by assuming the 30-band COSMOS-2015 photometric redshifts are correct (following the Dark Energy Survey and the Hyper Suprime-Cam Survey), we find the tension with Planck is alleviated. The robust determination of source redshift distributions remains one of the most challenging aspects for future cosmic shear surveys., Comment: 31 pages, 14 figures, accepted for publication by A&A; data products available at http://kids.strw.leidenuniv.nl

Published
2018
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21. COSMOGRAIL XVII: Time delays for the quadruply imaged quasar PG 1115+080

Author

Bonvin, V., Chan, J. H. H., Millon, M., Rojas, K., Courbin, F., Chen, G. C. -F., Fassnacht, C. D., Paic, E., Tewes, M., Chao, D. C. -Y., Chijani, M., Gilman, D., Gilmore, K., Williams, P., Buckley-Geer, E., Frieman, J., Marshall, P. J., Suyu, S. H., Treu, T., Hempel, A., Kim, S., Lachaume, R., Rabus, M., Anguita, T., Meylan, G., Motta, V., and Magain, P.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present time-delay estimates for the quadruply imaged quasar PG 1115+080. Our resuls are based on almost daily observations for seven months at the ESO MPIA 2.2m telescope at La Silla Observatory, reaching a signal-to-noise ratio of about 1000 per quasar image. In addition, we re-analyse existing light curves from the literature that we complete with an additional three seasons of monitoring with the Mercator telescope at La Palma Observatory. When exploring the possible source of bias we consider the so-called microlensing time delay, a potential source of systematic error so far never directly accounted for in previous time-delay publications. In fifteen years of data on PG 1115+080, we find no strong evidence of microlensing time delay. Therefore not accounting for this effect, our time-delay estimates on the individual data sets are in good agreement with each other and with the literature. Combining the data sets, we obtain the most precise time-delay estimates to date on PG 1115+080, with Dt(AB) = 8.3+1.5-1.6 days (18.7% precision), Dt(AC) = 9.9+1.1-1.1 days (11.1%) and Dt(BC) = 18.8+1.6-1.6 days (8.5%). Turning these time delays into cosmological constraints is done in a companion paper that makes use of ground-based Adaptive Optics (AO) with the Keck telescope., Comment: 15 pages, 6 figures, submitted to A&A. Comments welcome

Published
2018
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22. Weak lensing magnification of SpARCS galaxy clusters

Author

Tudorica, A., Hildebrandt, H., Tewes, M., Hoekstra, H., Morrison, C. B., Muzzin, A., Wilson, G., Yee, H. K. C., Lidman, C., Hicks, A., Nantais, J., Erben, T., van der Burg, R. F. J., and Demarco, R.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Measuring and calibrating relations between cluster observables is critical for resource-limited studies. The mass-richness relation of clusters offers an observationally inexpensive way of estimating masses. Its calibration is essential for cluster and cosmological studies, especially for high-redshift clusters. Weak gravitational lensing magnification is a promising and complementary method to shear studies, that can be applied at higher redshifts. We employed the weak lensing magnification method to calibrate the mass-richness relation up to a redshift of 1.4. We used the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS) galaxy cluster candidates ($0.21.0$ is 4.1$\sigma$; for the entire cluster sample we obtained an average M$_{200}$ of $1.28^{+0.23}_{-0.21}$ $\times 10^{14} \, \textrm{M}_{\odot}$. Our measurements demonstrated the feasibility of using weak lensing magnification as a viable tool for determining the average halo masses for samples of high redshift galaxy clusters. The results also established the success of using galaxy over-densities to select massive clusters at $z > 1$. Additional studies are necessary for further modelling of the various systematic effects we discussed., Comment: 13 pages, 13 figures, accepted for publication in A&A

Published
2017
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23. COSMOGRAIL XVI: Time delays for the quadruply imaged quasar DES J0408-5354 with high-cadence photometric monitoring

Author

Courbin, F., Bonvin, V., Buckley-Geer, E., Fassnacht, C. D., Frieman, J., Lin, H., Marshall, P. J., Suyu, S. H., Treu, T., Anguita, T., Motta, V., Meylan, G., Paic, E., Tewes, M., Agnello, A., Chao, D. C. -Y., Chijani, M., Gilman, D., Rojas, K., Williams, P., Hempel, A., Kim, S., Lachaume, R., Rabus, M., Abbott, T. M. C., Allam, S., Annis, J., Banerji, M., Bechtol, K., Benoit-Lévy, A., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., D'Andrea, C. B., da Costa, L. N., Davis, C., DePoy, D. L., Desai, S., Flaugher, B., Fosalba, P., Garcia-Bellido, J., Gaztanaga, E., Goldstein, D. A., Gruen, D., Gruendl, R. A., Gschwend, J., Gutierrez, G., Honscheid, K., James, D. J., Kuehn, K., Kuhlmann, S., Kuropatkin, N., Lahav, O., Lima, M., Maia, M. A. G., March, M., Marshall, J. L., McMahon, R. G., Menanteau, F., Miquel, R., Nord, B., Plazas, A. A., Sanchez, E., Scarpine, V., Schindler, R., Schubnell, M., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Tarle, G., Tucker, D. L., Walker, A. R., and Wester, W.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

We present time-delay measurements for the new quadruply imaged quasar DES J0408-5354, the first quadruply imaged quasar found in the Dark Energy Survey (DES). Our result is made possible by implementing a new observational strategy using almost daily observations with the MPIA 2.2m telescope at La Silla observatory and deep exposures reaching a signal-to-noise ratio of about 1000 per quasar image. This data quality allows us to catch small photometric variations (a few mmag rms) of the quasar, acting on temporal scales much shorter than microlensing, hence making the time delay measurement very robust against microlensing. In only 7 months we measure very accurately one of the time delays in DES J0408-5354: Dt(AB) = -112.1 +- 2.1 days (1.8%) using only the MPIA 2.2m data. In combination with data taken with the 1.2m Euler Swiss telescope, we also measure two delays involving the D component of the system Dt(AD) = -155.5 +- 12.8 days (8.2%) and Dt(BD) = -42.4 +- 17.6 days (41%), where all the error bars include systematics. Turning these time delays into cosmological constraints will require deep HST imaging or ground-based Adaptive Optics (AO), and information on the velocity field of the lensing galaxy., Comment: 9 pages, 5 figures, accepted for publication in Astronomy & Astrophysics

Published
2017
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24. COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses

Author

Courbin, F, Bonvin, V, Buckley-Geer, E, Fassnacht, CD, Frieman, J, Lin, H, Marshall, PJ, Suyu, SH, Treu, T, Anguita, T, Motta, V, Meylan, G, Paic, E, Tewes, M, Agnello, A, Chao, DC-Y, Chijani, M, Gilman, D, Rojas, K, Williams, P, Hempel, A, Kim, S, Lachaume, R, Rabus, M, Abbott, TMC, Allam, S, Annis, J, Banerji, M, Bechtol, K, Benoit-Lévy, A, Brooks, D, Burke, DL, Rosell, A Carnero, Kind, M Carrasco, Carretero, J, D’Andrea, CB, da Costa, LN, Davis, C, DePoy, DL, Desai, S, Flaugher, B, Fosalba, P, García-Bellido, J, Gaztanaga, E, Goldstein, DA, Gruen, D, Gruendl, RA, Gschwend, J, Gutierrez, G, Honscheid, K, James, DJ, Kuehn, K, Kuhlmann, S, Kuropatkin, N, Lahav, O, Lima, M, Maia, MAG, March, M, Marshall, JL, McMahon, RG, Menanteau, F, Miquel, R, Nord, B, Plazas, AA, Sanchez, E, Scarpine, V, Schindler, R, Schubnell, M, Sevilla-Noarbe, I, Smith, M, Soares-Santos, M, Sobreira, F, Suchyta, E, Tarle, G, Tucker, DL, Walker, AR, and Wester, W

Subjects
Space Sciences, Physical Sciences, methods: data analysis, gravitational lensing: strong, cosmological parameters, astro-ph.IM, astro-ph.GA, Astronomical and Space Sciences, Astronomy & Astrophysics, Astronomical sciences, Particle and high energy physics, Space sciences
Abstract

We present time-delay measurements for the new quadruple imaged quasar DES J04085354, the first quadruple imaged quasar found in the Dark Energy Survey (DES). Our result is made possible by implementing a new observational strategy using almost daily observations with the MPIA 2.2 m telescope at La Silla observatory and deep exposures reaching a signal-to-noise ratio of about 1000 per quasar image. This data qualityallows us to catch small photometric variations (a few mmag rms) of the quasar, acting on temporal scales much shorter than microlensing, and hence making the time delay measurement very robust against microlensing. In only seven months we very accurately measured one of the time delays in DES J04085354: - "t(AB) = 112.1 ± 2.1 days (1.8%) using only the MPIA 2.2 m data. In combination with data taken with the 1.2 m Euler Swiss telescope, we also measured two delays involving the D component of the system - "t(AD) = ± 12.8 days (8.2%) and - "t(BD) = 42.4 ± 17.6 days (41%), where all the error bars include systematics. Turning these time delays into cosmological constraints will require deep Hubble Space Telescope (HST) imaging or ground-based adaptive optics (AO), and information on the velocity field of the lensing galaxy.

Published
2018

27. H0LiCOW V. New COSMOGRAIL time delays of HE0435-1223: $H_0$ to 3.8% precision from strong lensing in a flat $\Lambda$CDM model

Author

Bonvin, V., Courbin, F., Suyu, S. H., Marshall, P. J., Rusu, C. E., Sluse, D., Tewes, M., Wong, K. C., Collett, T., Fassnacht, C. D., Treu, T., Auger, M. W., Hilbert, S., Koopmans, L. V. E., Meylan, G., Rumbaugh, N., Sonnenfeld, A., and Spiniello, C.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, 85A40, J.2
Abstract

We present a new measurement of the Hubble Constant H0 and other cosmological parameters based on the joint analysis of three multiply-imaged quasar systems with measured gravitational time delays. First, we measure the time delay of HE0435-1223 from 13-year light curves obtained as part of the COSMOGRAIL project. Companion papers detail the modeling of the main deflectors and line of sight effects, and how these data are combined to determine the time-delay distance of HE 0435-1223. Crucially, the measurements are carried out blindly with respect to cosmological parameters in order to avoid confirmation bias. We then combine the time-delay distance of HE0435-1223 with previous measurements from systems B1608+656 and RXJ1131-1231 to create a Time Delay Strong Lensing probe (TDSL). In flat $\Lambda$CDM with free matter and energy density, we find $H_0$ = 71.9 +2.4 -3.0 km/s/Mpc and $\Omega_{\Lambda}$ = 0.62 +0.24 -0.35 . This measurement is completely independent of, and in agreement with, the local distance ladder measurements of H0. We explore more general cosmological models combining TDSL with other probes, illustrating its power to break degeneracies inherent to other methods. The TDSL and Planck joint constraints are $H_0$ = 69.2 +1.4 -2.2 km/s/Mpc, $\Omega_{\Lambda}$ = 0.70 +0.01 -0.01 and $\Omega_k$ = 0.003 +0.004 -0.006 in open $\Lambda$CDM and $H_0$ = 79.0 +4.4 -4.2 km/s/Mpc, $\Omega_{de}$ = 0.77 +0.02 -0.03 and $w$ = -1.38 +0.14 -0.16 in flat $w$CDM. Combined with Planck and Baryon Acoustic Oscillation data, when relaxing the constraints on the numbers of relativistic species we find $N_{eff}$ = 3.34 +0.21 -0.21 and when relaxing the total mass of neutrinos we find 0.182 eV. In an open $w$CDM in combination with Planck and CMB lensing we find $H_0$ = 77.9 +5.0 -4.2 km/s/Mpc, $\Omega_{de}$ = 0.77 +0.03 -0.03, $\Omega_k$ = -0.003 +0.004 -0.004 and $w$ = -1.37 +0.18 -0.23., Comment: 19 pages, 7 figures, 4 tables. Accepted for publication in MNRAS. Light curves and simulated data can be downloaded at http://www.h0licow.org

Published
2016
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28. H0LiCOW II. Spectroscopic survey and galaxy-group identification of the strong gravitational lens system HE0435-1223

Author

Sluse, D., Sonnenfeld, A., Rumbaugh, N., Rusu, C. E., Fassnacht, C. D., Treu, T., Suyu, S. H., Wong, K. C., Auger, M. W., Bonvin, V., Collett, T., Courbin, F., Hilbert, S., Koopmans, L. V. E., Marshall, P. J., Meylan, G., Spiniello, C., and Tewes, M.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

Galaxies located in the environment or on the line of sight towards gravitational lenses can significantly affect lensing observables, and can lead to systematic errors on the measurement of $H_0$ from the time-delay technique. We present the results of a systematic spectroscopic identification of the galaxies in the field of view of the lensed quasar HE0435-1223, using the W. M. Keck, Gemini and ESO-Very Large telescopes. Our new catalog triples the number of known galaxy redshifts in the vicinity of the lens, expanding to 102 the number of measured redshifts for galaxies separated by less than 3 arcmin from the lens. We complement our catalog with literature data to gather redshifts up to 15 arcmin from the lens, and search for galaxy groups or clusters projected towards HE0435-1223. We confirm that the lens is a member of a small group that includes at least 12 galaxies, and find 8 other group candidates near the line of sight of the lens. The flexion shift, namely the shift of lensed images produced by high order perturbation of the lens potential, is calculated for each galaxy/group and used to identify which objects produce the largest perturbation of the lens potential. This analysis demonstrates that i) at most three of the five brightest galaxies projected within 12 arcsec of the lens need to be explicitly used in the lens models, and ii) the groups can be treated in the lens model as an external tidal field (shear) contribution., Comment: Version revised to address referee's comments, submitted to MNRAS, 21 pages (incl. Appendix). Data associated to the paper available from the H0LICOW website www.h0licow.org

Published
2016
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29. H0LiCOW I. $H_0$ Lenses in COSMOGRAIL's Wellspring: Program Overview

Author

Suyu, S. H., Bonvin, V., Courbin, F., Fassnacht, C. D., Rusu, C. E., Sluse, D., Treu, T., Wong, K. C., Auger, M. W., Ding, X., Hilbert, S., Marshall, P. J., Rumbaugh, N., Sonnenfeld, A., Tewes, M., Tihhonova, O., Agnello, A., Blandford, R. D., Chen, G. C. -F., Collett, T., Koopmans, L. V. E., Liao, K., Meylan, G., and Spiniello, C.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

Strong gravitational lens systems with time delays between the multiple images allow measurements of time-delay distances, which are primarily sensitive to the Hubble constant that is key to probing dark energy, neutrino physics, and the spatial curvature of the Universe, as well as discovering new physics. We present H0LiCOW ($H_0$ Lenses in COSMOGRAIL's Wellspring), a program that aims to measure $H_0$ with $<3.5\%$ uncertainty from five lens systems (B1608+656, RXJ1131-1231, HE0435-1223, WFI2033-4723 and HE1104-1805). We have been acquiring (1) time delays through COSMOGRAIL and Very Large Array monitoring, (2) high-resolution Hubble Space Telescope imaging for the lens mass modeling, (3) wide-field imaging and spectroscopy to characterize the lens environment, and (4) moderate-resolution spectroscopy to obtain the stellar velocity dispersion of the lenses for mass modeling. In cosmological models with one-parameter extension to flat $\Lambda$CDM, we expect to measure $H_0$ to $<3.5\%$ in most models, spatial curvature $\Omega_{\rm k}$ to 0.004, $w$ to 0.14, and the effective number of neutrino species to 0.2 (1$\sigma$ uncertainties) when combined with current CMB experiments. These are, respectively, a factor of $\sim15$, $\sim2$, and $\sim1.5$ tighter than CMB alone. Our data set will further enable us to study the stellar initial mass function of the lens galaxies, and the co-evolution of supermassive black holes and their host galaxies. This program will provide a foundation for extracting cosmological distances from the hundreds of time-delay lenses that are expected to be discovered in current and future surveys., Comment: 16 pages, 3 figures, submitted to MNRAS and revised based on referee's comments

Published
2016
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30. Stellar classification from single-band imaging using machine learning

Author

Kuntzer, T., Tewes, M., and Courbin, F.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

Information on the spectral types of stars is of great interest in view of the exploitation of space-based imaging surveys. In this article, we investigate the classification of stars into spectral types using only the shape of their diffraction pattern in a single broad-band image. We propose a supervised machine learning approach to this endeavour, based on principal component analysis (PCA) for dimensionality reduction, followed by artificial neural networks (ANNs) estimating the spectral type. Our analysis is performed with image simulations mimicking the Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) in the F606W and F814W bands, as well as the Euclid VIS imager. We first demonstrate this classification in a simple context, assuming perfect knowledge of the point spread function (PSF) model and the possibility of accurately generating mock training data for the machine learning. We then analyse its performance in a fully data-driven situation, in which the training would be performed with a limited subset of bright stars from a survey, and an unknown PSF with spatial variations across the detector. We use simulations of main-sequence stars with flat distributions in spectral type and in signal-to-noise ratio, and classify these stars into 13 spectral subclasses, from O5 to M5. Under these conditions, the algorithm achieves a high success rate both for Euclid and HST images, with typical errors of half a spectral class. Although more detailed simulations would be needed to assess the performance of the algorithm on a specific survey, this shows that stellar classification from single-band images is well possible., Comment: 10 pages, 9 figures, 2 tables, accepted in A&A

Published
2016
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31. Firedec: a two-channel finite-resolution image deconvolution algorithm

Author

Cantale, N., Courbin, F., Tewes, M., Jablonka., P., and Meylan, G.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

We present a two-channel deconvolution method that decomposes images into a parametric point-source channel and a pixelized extended-source channel. Based on the central idea of the deconvolution algorithm proposed by Magain, Courbin & Sohy (1998), the method aims at improving the resolution of the data rather than at completely removing the point spread function (PSF). Improvements over the original method include a better regularization of the pixel channel of the image, based on wavelet filtering and multiscale analysis, and a better controlled separation of the point source vs. the extended source. In addition, the method is able to simultaneously deconvolve many individual frames of the same object taken with different instruments under different PSF conditions. For this purpose, we introduce a general geometric transformation between individual images. This transformation allows the combination of the images without having to interpolate them. We illustrate the capability of our algorithm using real and simulated images with complex diffraction-limited PSF., Comment: Accepted in A&A. An application of the technique to real data is available in Cantale et al. http://arxiv.org/abs/1601.05192v1

Published
2016
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33. Euclid preparation. Measuring detailed galaxy morphologies for Euclid with Machine Learning

Author

Euclid Collaboration, Aussel, B., Kruk, S., Walmsley, M., Huertas-Company, M., Castellano, M., Conselice, C. J., Veneri, M. Delli, Sánchez, H. Domínguez, Duc, P. -A., Kuchner, U., La Marca, A., Margalef-Bentabol, B., Marleau, F. R., Stevens, G., Toba, Y., Tortora, C., Wang, L., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mainetti, G., Marcin, S., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Borgani, S., Borlaff, A. S., Bretonnière, H., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Coupon, J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., George, K., Giacomini, F., Gozaliasl, G., Gregorio, A., Guinet, D., Hall, A., Hildebrandt, H., Munoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Walton, Nicholas A., Peel, A., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Stanford, S. A., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Zinchenko, I. A., Euclid Collaboration, Aussel, B., Kruk, S., Walmsley, M., Huertas-Company, M., Castellano, M., Conselice, C. J., Veneri, M. Delli, Sánchez, H. Domínguez, Duc, P. -A., Kuchner, U., La Marca, A., Margalef-Bentabol, B., Marleau, F. R., Stevens, G., Toba, Y., Tortora, C., Wang, L., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mainetti, G., Marcin, S., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Borgani, S., Borlaff, A. S., Bretonnière, H., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Coupon, J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., George, K., Giacomini, F., Gozaliasl, G., Gregorio, A., Guinet, D., Hall, A., Hildebrandt, H., Munoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Walton, Nicholas A., Peel, A., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Stanford, S. A., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., and Zinchenko, I. A.

Abstract

The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in Euclid using Zoobot a convolutional neural network pretrained with 450000 galaxies from the Galaxy Zoo project. We adapted Zoobot for emulated Euclid images, generated based on Hubble Space Telescope COSMOS images, and with labels provided by volunteers in the Galaxy Zoo: Hubble project. We demonstrate that the trained Zoobot model successfully measures detailed morphology for emulated Euclid images. It effectively predicts whether a galaxy has features and identifies and characterises various features such as spiral arms, clumps, bars, disks, and central bulges. When compared to volunteer classifications Zoobot achieves mean vote fraction deviations of less than 12% and an accuracy above 91% for the confident volunteer classifications across most morphology types. However, the performance varies depending on the specific morphological class. For the global classes such as disk or smooth galaxies, the mean deviations are less than 10%, with only 1000 training galaxies necessary to reach this performance. For more detailed structures and complex tasks like detecting and counting spiral arms or clumps, the deviations are slightly higher, around 12% with 60000 galaxies used for training. In order to enhance the performance on complex morphologies, we anticipate that a larger pool of labelled galaxies is needed, which could be obtained using crowdsourcing. Finally, our findings imply that the model can be effectively adapted to new morphological labels. We demonstrate this adaptability by applying Zoobot to peculiar galaxies. In summary, our trained Zoobot CNN can readily predict morphological catalogues for Euclid images., Comment: 27 pages, 26 figures, 5 tables, submitted to A&A

Published
2024

34. Euclid preparation: TBD. The pre-launch Science Ground Segment simulation framework

Author

Euclid Collaboration, Serrano, S., Hudelot, P., Seidel, G., Pollack, J. E., Jullo, E., Torradeflot, F., Benielli, D., Fahed, R., Auphan, T., Carretero, J., Aussel, H., Casenove, P., Castander, F. J., Davies, J. E., Fourmanoit, N., Huot, S., Kara, A., Keihanen, E., Kermiche, S., Okumura, K., Zoubian, J., Ealet, A., Boucaud, A., Bretonniere, H., Casas, R., Clement, B., Duncan, C. A. J., George, K., Kiiveri, K., Kurki-Suonio, H., Kummel, M., Laugier, D., Mainetti, G., Mohr, J. J., Montoro, A., Neissner, C., Schirmer, M., Tallada-Crespi, P., Tonello, N., Venhola, A., Verderi, A., Zacchei, A., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Azzollini, R., Baldi, M., Bardelli, S., Basset, A., Battaglia, P., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., 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., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Kiessling, A., Kitching, T., Kohley, R., Kunz, M., Boulc'h, Q. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. -M., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Sauvage, M., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. -L., Taylor, A. N, Teplitz, H., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Gracia-Carpio, J., Liebing, P., Marcin, S., Mauri, N., Scottez, V., Tenti, M., Akrami, Y., Allevato, V., Baccigalupi, C., Ballardini, M., Bernardeau, F., Blanchard, A., Borgani, S., Borlaff, A. S., Bruton, S., Burigana, C., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Canas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Crocce, M., Davini, S., de la Torre, S., De Lucia, G., Desai, S., Desprez, G., Diaz-Sanchez, A., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Gregorio, A., Hildebrandt, H., Huertas-Company, M., Ilbert, O., Munoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Morris, P., Nadathur, S., Nucita, A. A., Pontinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Rusholme, B., Sakr, Z., Sanchez, A. G., Schneider, A., Sereno, M., Shulevski, A., Simon, P., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Tewes, M., Teyssier, R., Toft, S., Tucci, M., Valiviita, J., Viel, M., Zinchenko, I. A., Euclid Collaboration, Serrano, S., Hudelot, P., Seidel, G., Pollack, J. E., Jullo, E., Torradeflot, F., Benielli, D., Fahed, R., Auphan, T., Carretero, J., Aussel, H., Casenove, P., Castander, F. J., Davies, J. E., Fourmanoit, N., Huot, S., Kara, A., Keihanen, E., Kermiche, S., Okumura, K., Zoubian, J., Ealet, A., Boucaud, A., Bretonniere, H., Casas, R., Clement, B., Duncan, C. A. J., George, K., Kiiveri, K., Kurki-Suonio, H., Kummel, M., Laugier, D., Mainetti, G., Mohr, J. J., Montoro, A., Neissner, C., Schirmer, M., Tallada-Crespi, P., Tonello, N., Venhola, A., Verderi, A., Zacchei, A., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Azzollini, R., Baldi, M., Bardelli, S., Basset, A., Battaglia, P., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., 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., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Kiessling, A., Kitching, T., Kohley, R., Kunz, M., Boulc'h, Q. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. -M., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Sauvage, M., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. -L., Taylor, A. N, Teplitz, H., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Gracia-Carpio, J., Liebing, P., Marcin, S., Mauri, N., Scottez, V., Tenti, M., Akrami, Y., Allevato, V., Baccigalupi, C., Ballardini, M., Bernardeau, F., Blanchard, A., Borgani, S., Borlaff, A. S., Bruton, S., Burigana, C., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Canas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Crocce, M., Davini, S., de la Torre, S., De Lucia, G., Desai, S., Desprez, G., Diaz-Sanchez, A., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Gregorio, A., Hildebrandt, H., Huertas-Company, M., Ilbert, O., Munoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Morris, P., Nadathur, S., Nucita, A. A., Pontinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Rusholme, B., Sakr, Z., Sanchez, A. G., Schneider, A., Sereno, M., Shulevski, A., Simon, P., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Tewes, M., Teyssier, R., Toft, S., Tucci, M., Valiviita, J., Viel, M., and Zinchenko, I. A.

Abstract

The European Space Agency's Euclid mission is one of the upcoming generation of large-scale cosmology surveys, which will map the large-scale structure in the Universe with unprecedented precision. The development and validation of the SGS pipeline requires state-of-the-art simulations with a high level of complexity and accuracy that include subtle instrumental features not accounted for previously as well as faster algorithms for the large-scale production of the expected Euclid data products. In this paper, we present the Euclid SGS simulation framework as applied in a large-scale end-to-end simulation exercise named Science Challenge 8. Our simulation pipeline enables the swift production of detailed image simulations for the construction and validation of the Euclid mission during its qualification phase and will serve as a reference throughout operations. Our end-to-end simulation framework starts with the production of a large cosmological N-body & mock galaxy catalogue simulation. We perform a selection of galaxies down to I_E=26 and 28 mag, respectively, for a Euclid Wide Survey spanning 165 deg^2 and a 1 deg^2 Euclid Deep Survey. We build realistic stellar density catalogues containing Milky Way-like stars down to H<26. Using the latest instrumental models for both the Euclid instruments and spacecraft as well as Euclid-like observing sequences, we emulate with high fidelity Euclid satellite imaging throughout the mission's lifetime. We present the SC8 data set consisting of overlapping visible and near-infrared Euclid Wide Survey and Euclid Deep Survey imaging and low-resolution spectroscopy along with ground-based. This extensive data set enables end-to-end testing of the entire ground segment data reduction and science analysis pipeline as well as the Euclid mission infrastructure, paving the way to future scientific and technical developments and enhancements., Comment: 38 pages, 25 figures, A&A submitted

Published
2024

35. Euclid: Improving the efficiency of weak lensing shear bias calibration. Pixel noise cancellation and the response method on trial

Author

Jansen, H., Tewes, M., Schrabback, T., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., 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., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Joachimi, B., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., 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., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Miller, L., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. -M., 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., Skottfelt, J., Stanco, L., Tallada-Crespí, P., 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., Colodro-Conde, C., Scottez, V., Jansen, H., Tewes, M., Schrabback, T., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., 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., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Joachimi, B., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., 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., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Miller, L., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. -M., 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., Skottfelt, J., Stanco, L., Tallada-Crespí, P., 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., Colodro-Conde, C., and Scottez, V.

Abstract

To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. We study the efficiency of different noise cancellation methods that aim at reducing the simulation volume required to reach a given precision in the shear measurement. Explicitly, we compared fit methods with different noise cancellations and a method based on responses. We used GalSim to simulate galaxies both on a grid and at random positions in larger scenes. Placing the galaxies at random positions requires their detection, which we performed with SExtractor. On the grid, we neglected the detection step and, therefore, the potential detection bias arising from it. The shear of the simulated images was measured with the fast moment-based method KSB, for which we note deviations from purely linear shear measurement biases. For the estimation of uncertainties, we used bootstrapping as an empirical method. We find that each method we studied on top of shape noise cancellation can further increase the efficiency of calibration simulations. The improvement depends on the considered shear amplitude range and the type of simulations (grid-based or random positions). The response method on a grid for small shears provides the biggest improvement. In the more realistic case of randomly positioned galaxies, we still find an improvement factor of 70 for small shears using the response method. Alternatively, the runtime can be lowered by a factor of 7 already using pixel noise cancellation on top of shape noise cancellation. Furthermore, we demonstrate that the efficiency of shape noise cancellation can be enhanced in the presence of blending if entire scenes are rotated instead of individual galaxies., Comment: Accepted by A&A. 24 pages, 15+7 figures, Euclid standard paper

Published
2024

36. Euclid:Improving the efficiency of weak lensing shear bias calibration: Pixel noise cancellation and the response method on trial

Author

Jansen, H., Tewes, M., Schrabback, T., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., 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., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Joachimi, B., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., 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., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Miller, L., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. M., 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., Skottfelt, J., Stanco, L., Tallada-Crespí, P., 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., Colodro-Conde, C., Scottez, V., Jansen, H., Tewes, M., Schrabback, T., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Dinis, J., Dubath, F., 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., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Joachimi, B., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., 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., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Miller, L., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. M., 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., Skottfelt, J., Stanco, L., Tallada-Crespí, P., 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., Colodro-Conde, C., and Scottez, V.

Abstract

To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and consequently a substantial computational effort, seeking methods to speed the calibration up is valuable. We study the efficiency of different noise cancellation methods that aim at reducing the simulation volume required to reach a given precision in the shear measurement. The more efficient a method is, the faster we can estimate the relevant biases up to a required precision level. Explicitly, we compared fit methods with different noise cancellations and a method based on responses. We used GalSim to simulate galaxies both on a grid and at random positions in larger scenes. Placing the galaxies at random positions requires their detection, which we performed with SExtractor. On the grid, we neglected the detection step and, therefore, the potential detection bias arising from it. The shear of the simulated images was measured with the fast moment-based method KSB, for which we note deviations from purely linear shear measurement biases. For the estimation of uncertainties, we used bootstrapping as an empirical method. We extended the response-based approach to work on a wider range of shears and provide accurate estimates of selection biases. We find that each method we studied on top of shape noise cancellation can further increase the efficiency of calibration simulations. The improvement depends on the considered shear amplitude range and the type of simulations (grid-based or random positions). The response method on a grid for small shears provides the biggest improvement. Here the runtime for the estimation of multiplicative biases can be lowered by a factor of 145 compared to the benchmark simulations without any cancellation. In the more realistic case of randomly positioned galaxies, we still find

Published
2024

37. COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses XV. Assessing the achievability and precision of time-delay measurements

Author

Bonvin, V., Tewes, M., Courbin, F., Kuntzer, T., Sluse, D., and Meylan, G.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

COSMOGRAIL is a long-term photometric monitoring of gravitationally lensed QSOs aimed at implementing Refsdal's time-delay method to measure cosmological parameters, in particular H0. Given long and well sampled light curves of strongly lensed QSOs, time-delay measurements require numerical techniques whose quality must be assessed. To this end, and also in view of future monitoring programs or surveys such as the LSST, a blind signal processing competition named Time Delay Challenge 1 (TDC1) was held in 2014. The aim of the present paper, which is based on the simulated light curves from the TDC1, is double. First, we test the performance of the time-delay measurement techniques currently used in COSMOGRAIL. Second, we analyse the quantity and quality of the harvest of time delays obtained from the TDC1 simulations. To achieve these goals, we first discover time delays through a careful inspection of the light curves via a dedicated visual interface. Our measurement algorithms can then be applied to the data in an automated way. We show that our techniques have no significant biases, and yield adequate uncertainty estimates resulting in reduced chi2 values between 0.5 and 1.0. We provide estimates for the number and precision of time-delay measurements that can be expected from future time-delay monitoring campaigns as a function of the photometric signal-to-noise ratio and of the true time delay. We make our blind measurements on the TDC1 data publicly available, Comment: 11 pages, 8 figures, published in Astronomy & Astrophysics

Published
2015
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38. A Consistent Picture Emerges: A Compact X-ray Continuum Emission Region in the Gravitationally Lensed Quasar SDSS J0924+0219

Author

MacLeod, Chelsea L., Morgan, Christopher, Mosquera, A., Kochanek, C., Tewes, M., Courbin, F., Meylan, G., Chen, B., Dai, X., and Chartas, G.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We analyze the optical, UV, and X-ray microlensing variability of the lensed quasar SDSS J0924+0219 using six epochs of Chandra data in two energy bands (spanning 0.4-8.0 keV, or 1-20 keV in the quasar rest frame), 10 epochs of F275W (rest-frame 1089A) Hubble Space Telescope data, and high-cadence R-band (rest-frame 2770A) monitoring spanning eleven years. Our joint analysis provides robust constraints on the extent of the X-ray continuum emission region and the projected area of the accretion disk. The best-fit half-light radius of the soft X-ray continuum emission region is between 5x10^13 and 10^15 cm, and we find an upper limit of 10^15 cm for the hard X-rays. The best-fit soft-band size is about 13 times smaller than the optical size, and roughly 7 GM_BH/c^2 for a 2.8x10^8 M_sol black hole, similar to the results for other systems. We find that the UV emitting region falls in between the optical and X-ray emitting regions at 10^14 cm < r_1/2,UV < 3x10^15 cm. Finally, the optical size is significantly larger, by 1.5*sigma, than the theoretical thin-disk estimate based on the observed, magnification-corrected I-band flux, suggesting a shallower temperature profile than expected for a standard disk., Comment: Replaced with accepted version to ApJ

Published
2015
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39. Euclid: Improving the efficiency of weak lensing shear bias calibration

Author

Jansen, H., primary, Tewes, M., additional, Schrabback, T., additional, Aghanim, N., additional, Amara, A., additional, Andreon, S., additional, Auricchio, N., additional, Baldi, M., additional, Branchini, E., additional, Brescia, M., additional, Brinchmann, J., additional, Camera, S., additional, Capobianco, V., additional, Carbone, C., additional, Cardone, V. F., additional, Carretero, J., additional, Casas, S., additional, Castellano, M., additional, Cavuoti, S., additional, Cimatti, A., additional, Congedo, G., additional, Conversi, L., additional, Copin, Y., additional, Corcione, L., additional, Courbin, F., additional, Courtois, H. M., additional, Da Silva, A., additional, Degaudenzi, H., additional, Dinis, J., additional, Dubath, F., additional, Dupac, X., additional, Farina, M., additional, Farrens, S., additional, Ferriol, S., additional, Frailis, M., additional, Franceschi, E., additional, Fumana, M., additional, Galeotta, S., additional, Gillis, B., additional, Giocoli, C., additional, Grazian, A., additional, Grupp, F., additional, Haugan, S. V. H., additional, Hoekstra, H., additional, Holmes, W., additional, Hormuth, F., additional, Hornstrup, A., additional, Hudelot, P., additional, Jahnke, K., additional, Joachimi, B., additional, Kermiche, S., additional, Kiessling, A., additional, Kilbinger, M., additional, Kitching, T., additional, Kubik, B., additional, Kurki-Suonio, H., additional, Ligori, S., additional, Lilje, P. B., additional, Lindholm, V., additional, Lloro, I., additional, Maiorano, E., additional, Mansutti, O., additional, Marggraf, O., additional, Markovic, K., additional, Martinet, N., additional, Marulli, F., additional, Massey, R., additional, Medinaceli, E., additional, Mei, S., additional, Melchior, M., additional, Mellier, Y., additional, Meneghetti, M., additional, Merlin, E., additional, Meylan, G., additional, Miller, L., additional, Moresco, M., additional, Moscardini, L., additional, Munari, E., additional, Nakajima, R., additional, Niemi, S.-M., additional, Padilla, C., additional, Paltani, S., additional, Pasian, F., additional, Pedersen, K., additional, Pettorino, V., additional, Pires, S., additional, Polenta, G., additional, Poncet, M., additional, Raison, F., additional, Renzi, A., additional, Rhodes, J., additional, Riccio, G., additional, Romelli, E., additional, Roncarelli, M., additional, Rossetti, E., additional, Saglia, R., additional, Sapone, D., additional, Sartoris, B., additional, Schneider, P., additional, Secroun, A., additional, Seidel, G., additional, Serrano, S., additional, Sirignano, C., additional, Sirri, G., additional, Skottfelt, J., additional, Stanco, L., additional, Tallada-Crespí, P., additional, Tereno, I., additional, Toledo-Moreo, R., additional, Torradeflot, F., additional, Tutusaus, I., additional, Valentijn, E. A., additional, Valenziano, L., additional, Vassallo, T., additional, Veropalumbo, A., additional, Wang, Y., additional, Weller, J., additional, Zamorani, G., additional, Zoubian, J., additional, Colodro-Conde, C., additional, and Scottez, V., additional

Published
2024
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40. Imprints of the quasar structure in time-delay light curves: Microlensing-aided reverberation mapping

Author

Sluse, D. and Tewes, M.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

Owing to the advent of large area photometric surveys, the possibility to use broad band photometric data, instead of spectra, to measure the size of the broad line region of active galactic nuclei, has raised a large interest. We describe here a new method using time-delay lensed quasars where one or several images are affected by microlensing due to stars in the lensing galaxy. Because microlensing decreases (or increases) the flux of the continuum compared to the broad line region, it changes the contrast between these two emission components. We show that this effect can be used to effectively disentangle the intrinsic variability of those two regions, offering the opportunity to perform reverberation mapping based on single band photometric data. Based on simulated light curves generated using a damped random walk model of quasar variability, we show that measurement of the size of the broad line region can be achieved using this method, provided one spectrum has been obtained independently during the monitoring. This method is complementary to photometric reverberation mapping and could also be extended to multi-band data. Because the effect described above produces a variability pattern in difference light curves between pairs of lensed images which is correlated with the time-lagged continuum variability, it can potentially produce systematic errors in measurement of time delays between pairs of lensed images. Simple simulations indicate that time-delay measurement techniques which use a sufficiently flexible model for the extrinsic variability are not affected by this effect and produce accurate time delays., Comment: Accepted for publication in Astronomy and Astrophysics

Published
2014
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41. COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses XIV. Time delay of the doubly lensed quasar SDSS J1001+5027

Author

Kumar, S. Rathna, Tewes, M., Stalin, C. S., Courbin, F., Asfandiyarov, I., Meylan, G., Eulaers, E., Prabhu, T. P., Magain, P., Van Winckel, H., and Ehgamberdiev, Sh.

Subjects
Astrophysics - Cosmology and Extragalactic Astrophysics
Abstract

This paper presents optical R-band light curves and the time delay of the doubly imaged gravitationally lensed quasar SDSS J1001+5027 at a redshift of 1.838. We have observed this target for more than six years, between March 2005 and July 2011, using the 1.2-m Mercator Telescope, the 1.5-m telescope of the Maidanak Observatory, and the 2-m Himalayan Chandra Telescope. Our resulting light curves are composed of 443 independent epochs, and show strong intrinsic quasar variability, with an amplitude of the order of 0.2 magnitudes. From this data, we measure the time delay using five different methods, all relying on distinct approaches. One of these techniques is a new development presented in this paper. All our time-delay measurements are perfectly compatible. By combining them, we conclude that image A is leading B by 119.3 +/- 3.3 days (1 sigma, 2.8% uncertainty), including systematic errors. It has been shown recently that such accurate time-delay measurements offer a highly complementary probe of dark energy and spatial curvature, as they independently constrain the Hubble constant. The next mandatory step towards using SDSS J1001+5027 in this context will be the measurement of the velocity dispersion of the lensing galaxy, in combination with deep Hubble Space Telescope imaging., Comment: 8 pages, 7 figures, published in Astronomy & Astrophysics

Published
2013
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42. Cosmology from gravitational lens time delays and Planck data

Author

Suyu, S. H., Treu, T., Hilbert, S., Sonnenfeld, A., Auger, M. W., Blandford, R. D., Collett, T., Courbin, F., Fassnacht, C. D., Koopmans, L. V. E., Marshall, P. J., Meylan, G., Spiniello, C., and Tewes, M.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Under the assumption of a flat Lambda-CDM cosmology, recent data from the Planck satellite point toward a Hubble constant that is in tension with that measured by gravitational lens time delays and by the local distance ladder. Prosaically, this difference could arise from unknown systematic uncertainties in some of the measurements. More interestingly -- if systematics were ruled out -- resolving the tension would require a departure from the flat Lambda-CDM cosmology, introducing for example a modest amount of spatial curvature, or a non-trivial dark energy equation of state. To begin to address these issues, we present here an analysis of the gravitational lens RXJ1131-1231 that is improved in one particular regard: we examine the issue of systematic error introduced by an assumed lens model density profile. We use more flexible gravitational lens models with baryonic and dark matter components, and find that the exquisite Hubble Space Telescope image with thousands of intensity pixels in the Einstein ring and the stellar velocity dispersion of the lens contain sufficient information to constrain these more flexible models. The total uncertainty on the time-delay distance is 6.6% for a single system. We proceed to combine our improved time-delay distance measurements with the WMAP9 and Planck posteriors. In an open Lambda-CDM model, the data for RXJ1131-1231 in combination with Planck favor a flat universe with Omega_k = 0.00+0.01/-0.02 (68% CI). In a flat wCDM model, the combination of RXJ1131-1231 and Planck yields w = -1.52+0.19/-0.20 (68% CI)., Comment: 6 pages, 5 figures, accepted for publication in ApJL

Published
2013
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43. Dark energy with gravitational lens time delays

Author

Treu, T., Marshall, P. J., Cyr-Racine, F. -Y., Fassnacht, C. D., Keeton, C. R., Linder, E. V., Moustakas, L. A., Bradac, M., Buckley-Geer, E., Collett, T., Courbin, F., Dobler, G., Finley, D. A., Hjorth, J., Kochanek, C. S., Komatsu, E., Koopmans, L. V. E., Meylan, G., Natarajan, P., Oguri, M., Suyu, S. H., Tewes, M., Wong, K. C., Zabludoff, A. I., Zaritsky, D., Anguita, T., Brunner, R. J., Cabanac, R., Falco, E. E., Fritz, A., Seidel, G., Howell, D. A., Giocoli, C., Jackson, N., Lopez, S., Metcalf, R. B., Motta, V., and Verdugo, T.

Subjects
Astrophysics - Cosmology and Extragalactic Astrophysics
Abstract

Strong lensing gravitational time delays are a powerful and cost effective probe of dark energy. Recent studies have shown that a single lens can provide a distance measurement with 6-7 % accuracy (including random and systematic uncertainties), provided sufficient data are available to determine the time delay and reconstruct the gravitational potential of the deflector. Gravitational-time delays are a low redshift (z~0-2) probe and thus allow one to break degeneracies in the interpretation of data from higher-redshift probes like the cosmic microwave background in terms of the dark energy equation of state. Current studies are limited by the size of the sample of known lensed quasars, but this situation is about to change. Even in this decade, wide field imaging surveys are likely to discover thousands of lensed quasars, enabling the targeted study of ~100 of these systems and resulting in substantial gains in the dark energy figure of merit. In the next decade, a further order of magnitude improvement will be possible with the 10000 systems expected to be detected and measured with LSST and Euclid. To fully exploit these gains, we identify three priorities. First, support for the development of software required for the analysis of the data. Second, in this decade, small robotic telescopes (1-4m in diameter) dedicated to monitoring of lensed quasars will transform the field by delivering accurate time delays for ~100 systems. Third, in the 2020's, LSST will deliver 1000's of time delays; the bottleneck will instead be the aquisition and analysis of high resolution imaging follow-up. Thus, the top priority for the next decade is to support fast high resolution imaging capabilities, such as those enabled by the James Webb Space Telescope and next generation adaptive optics systems on large ground based telescopes., Comment: White paper submitted to SNOWMASS2013

Published
2013

44. COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses XII. Time delays of the doubly lensed quasars SDSS J1206+4332 and HS 2209+1914

Author

Eulaers, E., Tewes, M., Magain, P., Courbin, F., Asfandiyarov, I., Ehgamberdiev, Sh., Kumar, S. Rathna, Stalin, C. S., Prabhu, T. P., Meylan, G., and Van Winckel, H.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Aims. Within the framework of the COSMOGRAIL collaboration we present 7- and 8.5-year-long light curves and time-delay estimates for two gravitationally lensed quasars: SDSS J1206+4332 and HS 2209+1914. Methods. We monitored these doubly lensed quasars in the R-band using four telescopes: the Mercator, Maidanak, Himalayan Chandra, and Euler Telescopes, together spanning a period of 7 to 8.5 observing seasons from mid-2004 to mid-2011. The photometry of the quasar images was obtained through simultaneous deconvolution of these data. The time delays were determined from these resulting light curves using four very different techniques: a dispersion method, a spline fit, a regression difference technique, and a numerical model fit. This minimizes the bias that might be introduced by the use of a single method. Results. The time delay for SDSS J1206+4332 is Delta_t AB = 111.3 +/- 3 days with A leading B, confirming a previously published result within the error bars. For HS 2209+1914 we present a new time delay of Delta_t BA = 20.0 +/- 5 days with B leading A. Conclusions. The combination of data from up to four telescopes have led to well-sampled and nearly 9-season-long light curves, which were necessary to obtain these results, especially for the compact doubly lensed quasar HS 2209+1914., Comment: 10 pages, 10 figures, 6 tables

Published
2013
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45. The CORALIE survey for southern extrasolar planets XVII. New and updated long period and massive planets

Author

Marmier, M., Ségransan, D., Udry, S., Mayor, M., Pepe, F., Queloz, D., Lovis, C., Naef, D., Santos, N. C., Alonso, R., Alves, S., Berthet, S., Chazelas, B., Demory, B. -O., Dumusque, X., Eggenberger, A., Figueira, P., Gillon, M., Hagelberg, J., Lendl, M., Mardling, R. A., Mégevand, D., Neveu, M., Sahlmann, J., Sosnowska, D., Tewes, M., and Triaud, A. H. M. J.

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Since 1998, a planet-search program around main sequence stars within 50 pc in the southern hemisphere, is carried out with the CORALIE echelle spectrograph at La Silla Observatory. With an observing time span of more than 14 years, the CORALIE survey is now able to unveil Jovian planets on Jupiter's period domain. This growing period-interval coverage is important regarding to formation and migration models since observational constraints are still weak for periods beyond the ice line. Long-term precise Doppler measurements with the CORALIE echelle spectrograph, together with a few additional observations made with the HARPS spectrograph on the ESO 3.6m telescope, reveal radial velocity signatures of massive planetary companions in long period orbits. In this paper we present seven new planets orbiting HD27631, HD98649, HD106515A, HD166724, HD196067, HD219077, and HD220689 together with the CORALIE orbital parameters for three already known planets around HD10647, HD30562, and HD86226. The period range of the new planetary companions goes from 2200 to 5500 days and covers a mass domain between 1 and 10.5 MJup. Surprisingly, five of them present quite high eccentricities above e>0.57. A pumping scenario by Kozai mechanism may be invoked for HD106515Ab and HD196067b which are both orbiting stars in multiple systems. As the presence of a third massive body can't be inferred from the data of HD98649b, HD166724b, and HD219077b, the origin of the eccentricity of these systems remains unknown. Except for HD10647b, no constraint on the upper mass of the planets is provided by Hipparcos astrometric data. Finally it is interesting to note that the hosts of these long period planets show no metallicity excess., Comment: 14 pages, 16 figures, 4 tables, accepted for publication in Astronomy & Astrophysics

Published
2012
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46. Two accurate time-delay distances from strong lensing: Implications for cosmology

Author

Suyu, S. H., Auger, M. W., Hilbert, S., Marshall, P. J., Tewes, M., Treu, T., Fassnacht, C. D., Koopmans, L. V. E., Sluse, D., Blandford, R. D., Courbin, F., and Meylan, G.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Strong gravitational lenses with measured time delays between the multiple images and models of the lens mass distribution allow a one-step determination of the time-delay distance, and thus a measure of cosmological parameters. We present a blind analysis of the gravitational lens RXJ1131-1231 incorporating (1) the newly measured time delays from COSMOGRAIL, (2) archival HST imaging of the lens system, (3) a new velocity-dispersion measurement of the lens galaxy of 323+/-20km/s based on Keck spectroscopy, and (4) a characterization of the line-of-sight structures via observations of the lens' environment and ray tracing through the Millennium Simulation. Our blind analysis is designed to prevent experimenter bias. The joint analysis of the data sets allows a time-delay distance measurement to 6% precision that takes into account all known systematic uncertainties. In combination with the WMAP7 data set in flat wCDM cosmology, our unblinded cosmological constraints for RXJ1131-1231 are: H_0=80.0+5.8/-5.7km/s/Mpc, OmegaDE=0.79+/-0.03 and w=-1.25+0.17/-0.21. We find the results to be statistically consistent with those from the analysis of the gravitational lens B1608+656. The joint constraints from the two lenses and WMAP7 are H_0=75.2+4.4/-4.2km/s/Mpc, OmegaDE=0.76+0.02/-0.03 and w=-1.14+0.17/-0.20 in flat wCDM, and H_0=73.1+2.4/-3.6km/s/Mpc, OmegaL=0.75+0.01/-0.02 and OmegaK=0.003+0.005/-0.006 in open LCDM. Time-delay lenses constrain especially tightly the Hubble constant (5.7% and 4.0% respectively in wCDM and open LCDM) and curvature of the universe. They complement well other cosmological probes, and provide an independent check of unknown systematics. Our measurement of the Hubble constant is completely independent of those based on the local distance ladder method, providing an important consistency check of the standard cosmological model and of general relativity., Comment: 21 pages, 12 figures, minor revisions based on referee's comments, accepted for publication in ApJ

Published
2012
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47. COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses XIII: Time delays and 9-yr optical monitoring of the lensed quasar RX J1131-1231

Author

Tewes, M., Courbin, F., Meylan, G., Kochanek, C. S., Eulaers, E., Cantale, N., Mosquera, A. M., Magain, P., Van Winckel, H., Sluse, D., Cataldi, G., Voros, D., and Dye, S.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present the results from nine years of optically monitoring the gravitationally lensed z=0.658 quasar RX J1131-1231. The R-band light curves of the four individual images of the quasar were obtained using deconvolution photometry for a total of 707 epochs. Several sharp quasar variability features strongly constrain the time delays between the quasar images. Using three different numerical techniques, we measure these delays for all possible pairs of quasar images while always processing the four light curves simultaneously. For all three methods, the delays between the three close images A, B, and C are compatible with being 0, while we measure the delay of image D to be 91 days, with a fractional uncertainty of 1.5% (1 sigma), including systematic errors. Our analysis of random and systematic errors accounts in a realistic way for the observed quasar variability, fluctuating microlensing magnification over a broad range of temporal scales, noise properties, and seasonal gaps. Finally, we find that our time-delay measurement methods yield compatible results when applied to subsets of the data., Comment: 11 pages, 9 figures, minor additions to the text only, techniques and results remain unchanged, A&A in press

Published
2012
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48. COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses XI. Techniques for time delay measurement in presence of microlensing

Author

Tewes, M., Courbin, F., and Meylan, G.

Subjects
Astrophysics - Cosmology and Extragalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

Measuring time delays between the multiple images of gravitationally lensed quasars is now recognized as a competitive way to constrain the cosmological parameters, and it is complementary with other cosmological probes. This requires long and well sampled optical light curves of numerous lensed quasars, such as those obtained by the COSMOGRAIL collaboration. High-quality data from our monitoring campaign call for novel numerical techniques to robustly measure the delays, as well as the associated random and systematic uncertainties, even in the presence of microlensing variations. We propose three different point estimators to measure time delays, which are explicitly designed to handle light curves with extrinsic variability. These methods share a common formalism, which enables them to process data from n-image lenses. Since the estimators rely on significantly contrasting ideas, we expect them to be sensitive to different bias sources. For each method and data set, we empirically estimate both the precision and accuracy (bias) of the time delay measurement using simulated light curves with known time delays that closely mimic the observations. Finally, we test the self-consistency of our approach, and we demonstrate that our bias estimation is serviceable. These new methods, including the empirical uncertainty estimator, will represent the standard benchmark for analyzing the COSMOGRAIL light curves., Comment: 15 pages, 11 figures, stylistic improvements only, published in A&A

Published
2012
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49. A fast empirical method for galaxy shape measurements in weak lensing surveys

Author

Tewes, M., Cantale, N., Courbin, F., Kitching, T. D., and Meylan, G.

Subjects
Astrophysics - Cosmology and Extragalactic Astrophysics
Abstract

We describe a simple and fast method to correct ellipticity measurements of galaxies from the distortion by the instrumental and atmospheric point spread function (PSF), in view of weak lensing shear measurements. The method performs a classification of galaxies and associated PSFs according to measured shape parameters, and corrects the measured galaxy ellipticites by querying a large lookup table (LUT), built by supervised learning. We have applied this new method to the GREAT10 image analysis challenge, and present in this paper a refined solution that obtains the competitive quality factor of Q = 104, without any shear power spectrum denoising or training. Of particular interest is the efficiency of the method, with a processing time below 3 ms per galaxy on an ordinary CPU., Comment: 8 pages, 6 figures. Metric values updated according to the final GREAT10 analysis software (Kitching et al. 2012, MNRAS 423, 3163-3208), no qualitative changes. Associated code available at http://lastro.epfl.ch/megalut

Published
2012
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50. Image Analysis for Cosmology: Results from the GREAT10 Galaxy Challenge

Author

Kitching, T. D., Balan, S. T., Bridle, S., Cantale, N., Courbin, F., Eifler, T., Gentile, M., Gill, M. S. S., Harmeling, S., Heymans, C., Hirsch, M., Honscheid, K., Kacprzak, T., Kirkby, D., Margala, D., Massey, R. J., Melchior, P., Nurbaeva, G., Patton, K., Rhodes, J., Rowe, B. T. P., Taylor, A. N., Tewes, M., Viola, M., Witherick, D., Voigt, L., Young, J., and Zuntz, J.

Subjects
Astrophysics - Cosmology and Extragalactic Astrophysics
Abstract

In this paper we present results from the weak lensing shape measurement GRavitational lEnsing Accuracy Testing 2010 (GREAT10) Galaxy Challenge. This marks an order of magnitude step change in the level of scrutiny employed in weak lensing shape measurement analysis. We provide descriptions of each method tested and include 10 evaluation metrics over 24 simulation branches. GREAT10 was the first shape measurement challenge to include variable fields; both the shear field and the Point Spread Function (PSF) vary across the images in a realistic manner. The variable fields enable a variety of metrics that are inaccessible to constant shear simulations including a direct measure of the impact of shape measurement inaccuracies, and the impact of PSF size and ellipticity, on the shear power spectrum. To assess the impact of shape measurement bias for cosmic shear we present a general pseudo-Cl formalism, that propagates spatially varying systematics in cosmic shear through to power spectrum estimates. We also show how one-point estimators of bias can be extracted from variable shear simulations. The GREAT10 Galaxy Challenge received 95 submissions and saw a factor of 3 improvement in the accuracy achieved by shape measurement methods. The best methods achieve sub-percent average biases. We find a strong dependence in accuracy as a function of signal-to-noise, and indications of a weak dependence on galaxy type and size. Some requirements for the most ambitious cosmic shear experiments are met above a signal-to-noise ratio of 20. These results have the caveat that the simulated PSF was a ground-based PSF. Our results are a snapshot of the accuracy of current shape measurement methods and are a benchmark upon which improvement can continue. This provides a foundation for a better understanding of the strengths and limitations of shape measurement methods., Comment: Accepted to MNRAS

Published
2012
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