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1. Euclid preparation. Angular power spectra from discrete observations

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

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

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

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

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

4. Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method

Author: Campos, A., Yin, B., Dodelson, S., Amon, A., Alarcon, A., Sánchez, C., Bernstein, G. M., Giannini, G., Myles, J., Samuroff, S., Alves, O., Andrade-Oliveira, F., Bechtol, K., Becker, M. R., Blazek, J., Camacho, H., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Choi, A., Cordero, J., Davis, C., DeRose, J., Diehl, H. T., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elvin-Poole, J., Everett, S., Fang, X., Ferté, A., Friedrich, O., Gatti, M., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huang, H., Huff, E. M., Jarvis, M., Krause, E., Kuropatkin, N., Leget, P. -F., MacCrann, N., McCullough, J., Navarro-Alsina, A., Pandey, S., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Rosenfeld, R., Ross, A. J., Rykoff, E. S., Sanchez, J., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Wechsler, R. H., Yanny, B., Zhang, Y., Zuntz, J., Aguena, M., Annis, J., Bacon, D., Bocquet, S., Brooks, D., Burke, D. L., Carretero, J., Castander, F. J., Costanzi, M., da Costa, L. N., De Vicente, J., Doel, P., Ferrero, I., Flaugher, B., Frieman, J., García-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lima, M., Lin, H., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Ogando, R. L. C., Paterno, M., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Sanchez, E., Cid, D. Sanchez, Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., To, C., Vikram, V., and Weaverdyck, N.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.
Published: 2024

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

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

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

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

7. Increasing AGN sample completeness using long-term near-infrared variability

Author: Green, K., Elmer, E., Maltby, D. T., Almaini, O., Merrifield, M., and Hartley, W. G.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: In this work, we use 8 years of deep near-infrared imaging to select and study a new set of 601 active galaxies identified through long-term near-infrared (NIR) variability in the UKIDSS Ultra Deep Survey (UDS). These objects are compared to 710 X-ray bright AGN detected by the Chandra X-ray observatory. We show that infrared variability and X-ray emission select distinct sets of active galaxies, finding only a 37 per cent overlap of galaxies detected by both techniques and confirming NIR-variable AGN to be typically X-ray quiet. Examining the mass functions of the active galaxies shows that NIR variability detects AGN activity in galaxies over a significantly wider range of host stellar mass compared to X-ray detection. For example, at z $\sim$ 1, variable AGN are identified among approximately 1 per cent of galaxies in a roughly flat distribution above the stellar mass completeness limit (> 10$^{9}$M$_{\odot}$), while X-ray detection primarily identifies AGN in galaxies of higher mass (> 10$^{10}$M$_{\odot}$). We conclude that long-term near-infrared variability provides an important new tool for obtaining more complete samples of AGN in deep survey fields., Comment: Accepted for publication in MNRAS. 12 pages, 11 figures
Published: 2024
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8. Euclid: Early Release Observations -- A preview of the Euclid era through a galaxy cluster magnifying lens

Author: Atek, H., Gavazzi, R., Weaver, J. R., Diego, J. M., Schrabback, T., Hatch, N. A., Aghanim, N., Dole, H., Hartley, W. G., Taamoli, S., Congedo, G., Jimenez-Teja, Y., Cuillandre, J. -C., Bañados, E., Belladitta, S., Bowler, R. A. A., Franco, M., Jauzac, M., Mahler, G., Richard, J., Rocci, P. -F., Serjeant, S., Toft, S., Abriola, D., Bergamini, P., Biviano, A., Dimauro, P., Ezziati, M., Golden-Marx, J. B., Grillo, C., Hughes, A. C. N., Kang, Y., Kneib, J. -P., Lombardi, M., Mamon, G. A., McPartland, C. J. R., Meneghetti, M., Miyatake, H., Montes, M., Mortlock, D. J., Oesch, P. A., Okabe, N., Rosati, P., Taylor, A. N., Tarsitano, F., Weller, J., Kluge, M., Laureijs, R., Paltani, S., Saifollahi, T., Schirmer, M., Stone, C., Mora, A., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., 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., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Galeotta, S., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Hailey, M., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holliman, M. S., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Keihänen, E., Kermiche, S., Kiessling, A., Kitching, T., Kohley, R., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., 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., Maurogordato, S., McCracken, H. J., Mei, S., Mellier, Y., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Nakajima, R., Nichol, R. C., Niemi, S. -M., 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., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sapone, D., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Tallada-Crespí, P., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Zucca, E., Baccigalupi, C., Burigana, C., Castignani, G., Sakr, Z., Scottez, V., Viel, M., Simon, P., Stern, D., Martín-Fleitas, J., and Scott, D.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We present the first analysis of the Euclid Early Release Observations (ERO) program that targets fields around two lensing clusters, Abell 2390 and Abell 2764. We use VIS and NISP imaging to produce photometric catalogs for a total of $\sim 500\,000$ objects. The imaging data reach a $5\,\sigma$ typical depth in the range 25.1-25.4 AB in the NISP bands, and 27.1-27.3 AB in the VIS band. Using the Lyman-break method in combination with photometric redshifts, we identify $30$ Lyman-break galaxy (LBG) candidates at $z>6$ and 139 extremely red sources (ERSs), most likely at lower redshift. The deeper VIS imaging compared to NISP means we can routinely identify high-redshift Lyman breaks of the order of $3$ magnitudes, which reduces contamination by brown dwarf stars and low-redshift galaxies. Spectroscopic follow-up campaigns of such bright sources will help constrain both the bright end of the ultraviolet galaxy luminosity function and the quasar luminosity function at $z>6$, and constrain the physical nature of these objects. Additionally, we have performed a combined strong lensing and weak lensing analysis of A2390, and demonstrate how Euclid will contribute to better constraining the virial mass of galaxy clusters. From these data, we also identify optical and near-infrared counterparts of known $z>0.6$ clusters, which exhibit strong lensing features, establishing the ability of Euclid to characterize high-redshift clusters. Finally, we provide a glimpse of Euclid's ability to map the intracluster light out to larger radii than current facilities, enabling a better understanding of the cluster assembly history and mapping of the dark matter distribution. This initial dataset illustrates the diverse spectrum of legacy science that will be enabled by the Euclid survey., 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. 17 pages, 12 figures
Published: 2024

9. Euclid: Early Release Observations -- Programme overview and pipeline for compact- and diffuse-emission photometry

Author: Cuillandre, J. -C., Bertin, E., Bolzonella, M., Bouy, H., Gwyn, S., Isani, S., Kluge, M., Lai, O., Lançon, A., Lang, D. A., Laureijs, R., Saifollahi, T., Schirmer, M., Stone, C., Abdurro'uf, Aghanim, N., Altieri, B., Annibali, F., Atek, H., Awad, P., Baes, M., Bañados, E., Barrado, D., Belladitta, S., Belokurov, V., Boselli, A., Bournaud, F., Bovy, J., Bowler, R. A. A., Buenadicha, G., Buitrago, F., Cantiello, M., Carollo, D., Codis, S., Collins, M. L. M., Congedo, G., Dalessandro, E., de Lapparent, V., De Paolis, F., Diego, J. M., Dimauro, P., Dinis, J., Dole, H., Duc, P. -A., Erkal, D., Ezziati, M., Ferguson, A. M. N., Ferré-Mateu, A., Franco, A., Gavazzi, R., George, K., Gillard, W., Golden-Marx, J. B., Goldman, B., Gonzalez, A. H., Habas, R., Hartley, W. G., Hatch, N. A., Kohley, R., Hoar, J., Howell, J. M., Hunt, L. K., Jablonka, P., Jauzac, M., Kang, Y., Knapen, J. H., Kneib, J. -P., Kuzma, P. B., Larsen, S. S., Marchal, O., Martín-Fleitas, J., Marcos-Arenal, P., Marleau, F. R., Martín, E. L., Massari, D., McConnachie, A. W., Meneghetti, M., Miluzio, M., Carretero, J. Miro, Miyatake, H., Mondelin, M., Montes, M., Mora, A., Müller, O., Nally, C., Noeske, K., Nucita, A. A., Oesch, P. A., Oguri, M., Peletier, R. F., Poulain, M., Quilley, L., Racca, G. D., Rejkuba, M., Rhodes, J., Rocci, P. -F., Román, J., Sacquegna, S., Saremi, E., Scaramella, R., Schinnerer, E., Serjeant, S., Sola, E., Sorce, J. G., Tarsitano, F., Tereno, I., Toft, S., Tortora, C., Urbano, M., Venhola, A., Voggel, K., Weaver, J. R., Xu, X., Žerjal, M., Zöller, R., Andreon, S., Auricchio, N., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Bender, R., Bodendorf, C., Branchini, E., Brau-Nogue, S., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., 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., Cuby, J. -G., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Douspis, M., Duncan, C. A. J., Dupac, X., Dusini, S., Fabricius, M., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., 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., Mellier, Y., Meylan, G., Mohr, J. J., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Nichol, R. C., Niemi, S. -M., Padilla, C., Paltani, S., 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., Rossetti, E., Saglia, R., Sapone, D., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Toledo-Moreo, R., Tsyganov, A., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Wang, Y., Weller, J., Williams, O. R., Zamorani, G., Zucca, E., Baccigalupi, C., Burigana, C., Casenove, P., Liebing, P., Scottez, V., Simon, P., and Scott, D.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The Euclid ERO showcase Euclid's capabilities in advance of its main mission, targeting 17 astronomical objects, from galaxy clusters, nearby galaxies, globular clusters, to star-forming regions. A total of 24 hours observing time was allocated in the early months of operation, engaging the scientific community through an early public data release. We describe the development of the ERO pipeline to create visually compelling images while simultaneously meeting the scientific demands within months of launch, leveraging a pragmatic, data-driven development strategy. The pipeline's key requirements are to preserve the image quality and to provide flux calibration and photometry for compact and extended sources. The pipeline's five pillars are: removal of instrumental signatures; astrometric calibration; photometric calibration; image stacking; and the production of science-ready catalogues for both the VIS and NISP instruments. We report a PSF with a full width at half maximum of 0.16" in the optical and 0.49" in the three NIR bands. Our VIS mean absolute flux calibration is accurate to about 1%, and 10% for NISP due to a limited calibration set; both instruments have considerable colour terms. The median depth is 25.3 and 23.2 AB mag with a SNR of 10 for galaxies, and 27.1 and 24.5 AB mag at an SNR of 5 for point sources for VIS and NISP, respectively. Euclid's ability to observe diffuse emission is exceptional due to its extended PSF nearly matching a pure diffraction halo, the best ever achieved by a wide-field, high-resolution imaging telescope. Euclid offers unparalleled capabilities for exploring the LSB Universe across all scales, also opening a new observational window in the NIR. Median surface-brightness levels of 29.9 and 28.3 AB mag per square arcsec are achieved for VIS and NISP, respectively, for detecting a 10 arcsec x 10 arcsec extended feature at the 1 sigma level., Comment: Submitted to A&A, 44 pages, 36 figures - 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

10. 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

11. Euclid. IV. The NISP Calibration Unit

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

12. Euclid. III. The NISP Instrument

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

13. 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. 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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. 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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

14. 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

15. Dark Energy Survey Year 3 results: simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps II. Cosmological results

Author: Gatti, M., Campailla, G., Jeffrey, N., Whiteway, L., Porredon, A., Prat, J., Williamson, J., Raveri, M., Jain, B., Ajani, V., Giannini, G., Yamamoto, M., Zhou, C., Blazek, J., Anbajagane, D., Samuroff, S., Kacprzak, T., Alarcon, A., Amon, A., Bechtol, K., Becker, M., Bernstein, G., Campos, A., Chang, C., Chen, R., Choi, A., Davis, C., Derose, J., Diehl, H. T., Dodelson, S., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferte, A., Gruen, D., Gruendl, R., Harrison, I., Hartley, W. G., Herner, K., Huff, E. M., Jarvis, M., Kuropatkin, N., Leget, P. F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Rollins, R. P., Roodman, A., Sanchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Abbott, T. M. C., Aguena, M., Allam, S. S., Alves, O., Andrade-Oliveira, F., Bacon, D., Bocquet, S., Brooks, D., Rosell, A. Carnero, Carretero, J., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Ferrero, I., Frieman, J., García-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Lee, S., Marshall, J. L., Mena-Fernández, J., Miquel, R., Pieres, A., Malagón, A. A. Plazas, Sanchez, E., Cid, D. Sanchez, Schubnell, M., Smith, M., Suchyta, E., Tarle, G., Weaverdyck, N., Weller, J., and Wiseman, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years (Y3) of the Dark Energy Survey (DES). We implement: 1) second and third moments; 2) wavelet phase harmonics; 3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven $\nu w$CDM cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the Figure of Merit $\textrm{FoM}(S_8, \Omega_{\textrm{m}})$ is improved by 70 percent ($\Lambda$CDM) and 90 percent ($w$CDM). When all the summary statistics are combined, we achieve a 2 percent constraint on the amplitude of fluctuations parameter $S_8 \equiv \sigma_8 (\Omega_{\textrm{m}}/0.3)^{0.5}$, obtaining $S_8 = 0.794 \pm 0.017$ ($\Lambda$CDM) and $S_8 = 0.817 \pm 0.021$ ($w$CDM). The constraints from different statistics are shown to be internally consistent (with a $p$-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the DES Y3 data, finding good consistency; we also compare with results from external datasets, such as \planck{} constraints from the Cosmic Microwave Background, finding statistical agreement, with discrepancies no greater than $<2.2\sigma$., Comment: 24 pages, 13 figures, to be submitted to PRD. Comments welcome!
Published: 2024

16. Weak lensing combined with the kinetic Sunyaev Zel'dovich effect: A study of baryonic feedback

Author: Bigwood, L., Amon, A., Schneider, A., Salcido, J., McCarthy, I. G., Preston, C., Sanchez, D., Sijacki, D., Schaan, E., Ferraro, S., Battaglia, N., Chen, A., Dodelson, S., Roodman, A., Pieres, A., Ferte, A., Alarcon, A., Drlica-Wagner, A., Choi, A., Navarro-Alsina, A., Campos, A., Ross, A. J., Rosell, A. Carnero, Yin, B., Yanny, B., Sanchez, C., Chang, C., Davis, C., Doux, C., Gruen, D., Rykoff, E. S., Huff, E. M., Sheldon, E., Tarsitano, F., Andrade-Oliveira, F., Bernstein, G. M., Giannini, G., Diehl, H. T., Huang, H., Harrison, I., Sevilla-Noarbe, I., Tutusaus, I., Elvin-Poole, J., McCullough, J., Zuntz, J., Blazek, J., DeRose, J., Cordero, J., Prat, J., Myles, J., Eckert, K., Bechtol, K., Herner, K., Secco, L. F., Gatti, M., Raveri, M., Kind, M. Carrasco, Becker, M. R., Troxel, M. A., Jarvis, M., MacCrann, N., Friedrich, O., Alves, O., Leget, P. -F., Chen, R., Rollins, R. P., Wechsler, R. H., Gruendl, R. A., Cawthon, R., Allam, S., Bridle, S. L., Pandey, S., Everett, S., Shin, T., Hartley, W. G., Fang, X., Zhang, Y., Aguena, M., Annis, J., Bacon, D., Bertin, E., Bocquet, S., Brooks, D., Carretero, J., Castander, F. J., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Desai, S., Doel, P., Ferrero, I., Flaugher, B., Frieman, J., Garcia-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., James, D. J., Kuehn, K., Lahav, O., Lee, S., Marshall, J. L., Mena-Fernandez, J., Miquel, R., Muir, J., Paterno, M., Malagon, A. A. Plazas, Porredon, A., Romer, A. K., Samuroff, S., Sanchez, E., Cid, D. Sanchez, Smith, M., Soares-Santos, M., Suchyta, E., Swanson, M. E. C., Tarle, G., To, C., Weaverdyck, N., Weller, J., Wiseman, P., and Yamamoto, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: Extracting precise cosmology from weak lensing surveys requires modelling the non-linear matter power spectrum, which is suppressed at small scales due to baryonic feedback processes. However, hydrodynamical galaxy formation simulations make widely varying predictions for the amplitude and extent of this effect. We use measurements of Dark Energy Survey Year 3 weak lensing (WL) and Atacama Cosmology Telescope DR5 kinematic Sunyaev-Zel'dovich (kSZ) to jointly constrain cosmological and astrophysical baryonic feedback parameters using a flexible analytical model, `baryonification'. First, using WL only, we compare the $S_8$ constraints using baryonification to a simulation-calibrated halo model, a simulation-based emulator model and the approach of discarding WL measurements on small angular scales. We find that model flexibility can shift the value of $S_8$ and degrade the uncertainty. The kSZ provides additional constraints on the astrophysical parameters and shifts $S_8$ to $S_8=0.823^{+0.019}_{-0.020}$, a higher value than attained using the WL-only analysis. We measure the suppression of the non-linear matter power spectrum using WL + kSZ and constrain a mean feedback scenario that is more extreme than the predictions from most hydrodynamical simulations. We constrain the baryon fractions and the gas mass fractions and find them to be generally lower than inferred from X-ray observations and simulation predictions. We conclude that the WL + kSZ measurements provide a new and complementary benchmark for building a coherent picture of the impact of gas around galaxies across observations.
Published: 2024

17. Dark Energy Survey: Galaxy Sample for the Baryonic Acoustic Oscillation Measurement from the Final Dataset

Author: Mena-Fernández, J., Rodríguez-Monroy, M., Avila, S., Porredon, A., Chan, K. C., Camacho, H., Weaverdyck, N., Sevilla-Noarbe, I., Sanchez, E., Cipriano, L. Toribio San, De Vicente, J., Ferrero, I., Cawthon, R., Rosell, A. Carnero, Elvin-Poole, J., Giannini, G., Adamow, M., Bechtol, K., Drlica-Wagner, A., Gruendl, R. A., Hartley, W. G., Pieres, A., Ross, A. J., Rykoff, E. S., Sheldon, E., Yanny, B., Abbott, T. M. C., Aguena, M., Allam, S., Alves, O., Amon, A., Andrade-Oliveira, F., Annis, J., Bacon, D., Blazek, J., Bocquet, S., Brooks, D., Carretero, J., Castander, F. J., Conselice, C., Crocce, M., da Costa, L. N., Pereira, M. E. S., Davis, T. M., Deiosso, N., Desai, S., Diehl, H. T., Dodelson, S., Doux, C., Everett, S., Frieman, J., García-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., Kuehn, K., Lahav, O., Lee, S., Lidman, C., Lin, H., Marshall, J. L., Menanteau, F., Miquel, R., Myles, J., Ogando, R. L. C., Palmese, A., Percival, W. J., Malagón, A. A. Plazas, Roodman, A., Rosenfeld, R., Samuroff, S., Cid, D. Sanchez, Santiago, B., Schubnell, M., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., Tucker, D. L., Walker, A. R., Weller, J., Wiseman, P., and Yamamoto, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: In this paper we present and validate the galaxy sample used for the analysis of the baryon acoustic oscillation (BAO) signal in the Dark Energy Survey (DES) Y6 data. The definition is based on a color and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.6, while ensuring a high-quality photo-$z$ determination. The optimization is performed using a Fisher forecast algorithm, finding the optimal $i$-magnitude cut to be given by $i$<19.64+2.894$z_{\rm ph}$. For the optimal sample, we forecast an increase in precision in the BAO measurement of $\sim$25% with respect to the Y3 analysis. Our BAO sample has a total of 15,937,556 galaxies in the redshift range 0.6<$z_{\rm ph}$<1.2, and its angular mask covers 4,273.42 deg${}^2$ to a depth of $i$=22.5. We validate its redshift distributions with three different methods: directional neighborhood fitting algorithm (DNF), which is our primary photo-$z$ estimation; direct calibration with spectroscopic redshifts from VIPERS; and clustering redshift using SDSS galaxies. The fiducial redshift distribution is a combination of these three techniques performed by modifying the mean and width of the DNF distributions to match those of VIPERS and clustering redshift. In this paper we also describe the methodology used to mitigate the effect of observational systematics, which is analogous to the one used in the Y3 analysis. This paper is one of the two dedicated to the analysis of the BAO signal in DES Y6. In its companion paper, we present the angular diameter distance constraints obtained through the fitting to the BAO scale., Comment: 23 pages, 10 figures. Submitted to PRD
Published: 2024

18. Dark Energy Survey: A 2.1% measurement of the angular Baryonic Acoustic Oscillation scale at redshift $z_{\rm eff}$=0.85 from the final dataset

Author: DES Collaboration, Abbott, T. M. C., Adamow, M., Aguena, M., Allam, S., Alves, O., Amon, A., Andrade-Oliveira, F., Asorey, J., Avila, S., Bacon, D., Bechtol, K., Bernstein, G. M., Bertin, E., Blazek, J., Bocquet, S., Brooks, D., Burke, D. L., Camacho, H., Rosell, A. Carnero, Carollo, D., Carretero, J., Castander, F. J., Cawthon, R., Chan, K. C., Chang, C., Conselice, C., Costanzi, M., Crocce, M., da Costa, L. N., Pereira, M. E. S., Davis, T. M., De Vicente, J., Deiosso, N., Desai, S., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Elvin-Poole, J., Everett, S., Ferrero, I., Ferté, A., Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gaztanaga, E., Giannini, G., Gruendl, R. A., Gutierrez, G., Hartley, W. G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., James, D. J., Kent, S., Kuehn, K., Lahav, O., Lee, S., Lidman, C., Lin, H., Marshall, J. L., Martini, P., Mena-Fernández, J., Menanteau, F., Miquel, R., Mohr, J. J., Myles, J., Nichol, R. C., Ogando, R. L. C., Palmese, A., Percival, W. J., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Prat, J., Rodríguez-Monroy, M., Romer, A. K., Roodman, A., Rosenfeld, R., Ross, A. J., Rykoff, E. S., Sako, M., Samuroff, S., Sánchez, C., Sanchez, E., Cid, D. Sanchez, Santiago, B., Schubnell, M., Sevilla-Noarbe, I., Sheldon, E., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., Cipriano, L. Toribio San, Troxel, M. A., Tucker, B. E., Tucker, D. L., Walker, A. R., Weaverdyck, N., Weller, J., Wiseman, P., and Yanny, B.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present the angular diameter distance measurement obtained with the Baryonic Acoustic Oscillation feature from galaxy clustering in the completed Dark Energy Survey, consisting of six years (Y6) of observations. We use the Y6 BAO galaxy sample, optimized for BAO science in the redshift range 0.6<$z$<1.2, with an effective redshift at $z_{\rm eff}$=0.85 and split into six tomographic bins. The sample has nearly 16 million galaxies over 4,273 square degrees. Our consensus measurement constrains the ratio of the angular distance to sound horizon scale to $D_M(z_{\rm eff})/r_d$ = 19.51$\pm$0.41 (at 68.3% confidence interval), resulting from comparing the BAO position in our data to that predicted by Planck $\Lambda$CDM via the BAO shift parameter $\alpha=(D_M/r_d)/(D_M/r_d)_{\rm Planck}$. To achieve this, the BAO shift is measured with three different methods, Angular Correlation Function (ACF), Angular Power Spectrum (APS), and Projected Correlation Function (PCF) obtaining $\alpha=$ 0.952$\pm$0.023, 0.962$\pm$0.022, and 0.955$\pm$0.020, respectively, which we combine to $\alpha=$ 0.957$\pm$0.020, including systematic errors. When compared with the $\Lambda$CDM model that best fits Planck data, this measurement is found to be 4.3% and 2.1$\sigma$ below the angular BAO scale predicted. To date, it represents the most precise angular BAO measurement at $z$>0.75 from any survey and the most precise measurement at any redshift from photometric surveys. The analysis was performed blinded to the BAO position and it is shown to be robust against analysis choices, data removal, redshift calibrations and observational systematics., Comment: Submitted to PRD, 39 pages, 12 figures
Published: 2024

19. The SRG/eROSITA All-Sky Survey: Dark Energy Survey Year 3 Weak Gravitational Lensing by eRASS1 selected Galaxy Clusters

Author: Grandis, S., Ghirardini, V., Bocquet, S., Garrel, C., Mohr, J. J., Liu, A., Kluge, M., Kimmig, L., Reiprich, T. H., Alarcon, A., Amon, A., Artis, E., Bahar, Y. E., Balzer, F., Bechtol, K., Becker, M. R., Bernstein, G., Bulbul, E., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Chiu, I., Choi, A., Clerc, N., Comparat, J., Cordero, J., Davis, C., Derose, J., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Elvin-Poole, J., Everett, S., Ferte, A., Gatt, M., Giannini, G., Giles, P., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huf, E. M., Kleinebreil, F., Kuropatkin, N., Leget, P. F., Maccrann, N., Mccullough, J., Merloni, A., Myles, J., Nandra, K., Navarro-Alsina, A., Okabe, N., Pacaud, F., Pandey, S., Prat, J., Predehl, P., Ramos, M., Raveri, M., Rollins, R. P., Roodman, A., Ross, A. J., Rykoff, E. S., Sanchez, C., Sanders, J., Schrabback, T., Secco, L. F., Seppi, R., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M., Tutusaus, I., Varga, T. N., Wu, H., Yanny, B., Yin, B., Zhang, X., Zhang, Y., Alves, O., Bhargava, S., Brooks, D., Burke, D. L., Carretero, J., Costanzi, M., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Desai, S., Doel, P., Ferrero, I., Flaugher, B., Friedel, D., Frieman, J., García-Bellido, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Jeffrey, N., Lahav, O., Lee, S., Marshall, J. L., Menanteau, F., Ogando, R. L. C., Pieres, A., Malagón, A. A. Plazas, Romer, A. K., Sanchez, E., Schubnell, M., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Weaverdyck, N., and Weller, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Number counts of galaxy clusters across redshift are a powerful cosmological probe, if a precise and accurate reconstruction of the underlying mass distribution is performed -- a challenge called mass calibration. With the advent of wide and deep photometric surveys, weak gravitational lensing by clusters has become the method of choice to perform this measurement. We measure and validate the weak gravitational lensing (WL) signature in the shape of galaxies observed in the first 3 years of the DES Y3 caused by galaxy clusters selected in the first all-sky survey performed by SRG/eROSITA. These data are then used to determine the scaling between X-ray photon count rate of the clusters and their halo mass and redshift. We empirically determine the degree of cluster member contamination in our background source sample. The individual cluster shear profiles are then analysed with a Bayesian population model that self-consistently accounts for the lens sample selection and contamination, and includes marginalization over a host of instrumental and astrophysical systematics. To quantify the accuracy of the mass extraction of that model, we perform mass measurements on mock cluster catalogs with realistic synthetic shear profiles. This allows us to establish that hydro-dynamical modelling uncertainties at low lens redshifts ($z<0.6$) are the dominant systematic limitation. At high lens redshift the uncertainties of the sources' photometric redshift calibration dominate. With regard to the X-ray count rate to halo mass relation, we constrain all its parameters. This work sets the stage for a joint analysis with the number counts of eRASS1 clusters to constrain a host of cosmological parameters. We demonstrate that WL mass calibration of galaxy clusters can be performed successfully with source galaxies whose calibration was performed primarily for cosmic shear experiments., Comment: 27 pages, 18 figures, 2 appendices, submitted to A\&A
Published: 2024
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20. The Dark Energy Survey: Cosmology Results With ~1500 New High-redshift Type Ia Supernovae Using The Full 5-year Dataset

Author: DES Collaboration, Abbott, T. M. C., Acevedo, M., Aguena, M., Alarcon, A., Allam, S., Alves, O., Amon, A., Andrade-Oliveira, F., Annis, J., Armstrong, P., Asorey, J., Avila, S., Bacon, D., Bassett, B. A., Bechtol, K., Bernardinelli, P. H., Bernstein, G. M., Bertin, E., Blazek, J., Bocquet, S., Brooks, D., Brout, D., Buckley-Geer, E., Burke, D. L., Camacho, H., Camilleri, R., Campos, A., Rosell, A. Carnero, Carollo, D., Carr, A., Carretero, J., Castander, F. J., Cawthon, R., Chang, C., Chen, R., Choi, A., Conselice, C., Costanzi, M., da Costa, L. N., Crocce, M., Davis, T. M., DePoy, D. L., Desai, S., Diehl, H. T., Dixon, M., Dodelson, S., Doel, P., Doux, C., Drlica-Wagner, A., Elvin-Poole, J., Everett, S., Ferrero, I., Ferté, A., Flaugher, B., Foley, R. J., Fosalba, P., Friedel, D., Frieman, J., Frohmaier, C., Galbany, L., García-Bellido, J., Gatti, M., Gaztanaga, E., Giannini, G., Glazebrook, K., Graur, O., Gruen, D., Gruendl, R. A., Gutierrez, G., Hartley, W. G., Herner, K., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., Jain, B., James, D. J., Jeffrey, N., Kasai, E., Kelsey, L., Kent, S., Kessler, R., Kim, A. G., Kirshner, R. P., Kovacs, E., Kuehn, K., Lahav, O., Lee, J., Lee, S., Lewis, G. F., Li, T. S., Lidman, C., Lin, H., Malik, U., Marshall, J. L., Martini, P., Mena-Fernández, J., Menanteau, F., Miquel, R., Mohr, J. J., Mould, J., Muir, J., Möller, A., Neilsen, E., Nichol, R. C., Nugent, P., Ogando, R. L. C., Palmese, A., Pan, Y. -C., Paterno, M., Percival, W. J., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Popovic, B., Porredon, A., Prat, J., Qu, H., Raveri, M., Rodríguez-Monroy, M., Romer, A. K., Roodman, A., Rose, B., Sako, M., Sanchez, E., Cid, D. Sanchez, Schubnell, M., Scolnic, D., Sevilla-Noarbe, I., Shah, P., Smith, J. Allyn., Smith, M., Soares-Santos, M., Suchyta, E., Sullivan, M., Suntzeff, N., Swanson, M. E. C., Sánchez, B. O., Tarle, G., Taylor, G., Thomas, D., To, C., Toy, M., Troxel, M. A., Tucker, B. E., Tucker, D. L., Uddin, S. A., Vincenzi, M., Walker, A. R., Weaverdyck, N., Wechsler, R. H., Weller, J., Wester, W., Wiseman, P., Yamamoto, M., Yuan, F., Zhang, B., and Zhang, Y.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present cosmological constraints from the sample of Type Ia supernovae (SN Ia) discovered during the full five years of the Dark Energy Survey (DES) Supernova Program. In contrast to most previous cosmological samples, in which SN are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being a SN Ia, we find 1635 DES SNe in the redshift range $0.100.5$ SNe compared to the previous leading compilation of Pantheon+, and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints we combine the DES supernova data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning $0.025
Published: 2024

21. SPT Clusters with DES and HST Weak Lensing. II. Cosmological Constraints from the Abundance of Massive Halos

Author: Bocquet, S., Grandis, S., Bleem, L. E., Klein, M., Mohr, J. J., Schrabback, T., Abbott, T. M. C., Ade, P. A. R., Aguena, M., Alarcon, A., Allam, S., Allen, S. W., Alves, O., Amon, A., Anderson, A. J., Annis, J., Ansarinejad, B., Austermann, J. E., Avila, S., Bacon, D., Bayliss, M., Beall, J. A., Bechtol, K., Becker, M. R., Bender, A. N., Benson, B. A., Bernstein, G. M., Bhargava, S., Bianchini, F., Brodwin, M., Brooks, D., Bryant, L., Campos, A., Canning, R. E. A., Carlstrom, J. E., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Cawthon, R., Chang, C. L., Chang, C., Chaubal, P., Chen, R., Chiang, H. C., Choi, A., Chou, T-L., Citron, R., Moran, C. Corbett, Cordero, J., Costanzi, M., Crawford, T. M., Crites, A. T., da Costa, L. N., Pereira, M. E. S., Davis, C., Davis, T. M., DeRose, J., Desai, S., de Haan, T., Diehl, H. T., Dobbs, M. A., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Elvin-Poole, J., Everett, S., Everett, W., Ferrero, I., Ferté, A., Flores, A. M., Frieman, J., Gallicchio, J., García-Bellido, J., Gatti, M., George, E. M., Giannini, G., Gladders, M. D., Gruen, D., Gruendl, R. A., Gupta, N., Gutierrez, G., Halverson, N. W., Harrison, I., Hartley, W. G., Herner, K., Hinton, S. R., Holder, G. P., Hollowood, D. L., Holzapfel, W. L., Honscheid, K., Hrubes, J. D., Huang, N., Hubmayr, J., Huff, E. M., Huterer, D., Irwin, K. D., James, D. J., Jarvis, M., Khullar, G., Kim, K., Knox, L., Kraft, R., Krause, E., Kuehn, K., Kuropatkin, N., Kéruzoré, F., Lahav, O., Lee, A. T., Leget, P. -F., Li, D., Lin, H., Lowitz, A., MacCrann, N., Mahler, G., Mantz, A., Marshall, J. L., McCullough, J., McDonald, M., McMahon, J. J., Mena-Fernández, J., Menanteau, F., Meyer, S. S., Miquel, R., Montgomery, J., Myles, J., Natoli, T., Navarro-Alsina, A., Nibarger, J. P., Noble, G. I., Novosad, V., Ogando, R. L. C., Omori, Y., Padin, S., Pandey, S., Paschos, P., Patil, S., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Prat, J., Pryke, C., Raveri, M., Reichardt, C. L., Roberson, J., Rollins, R. P., Romero, C., Roodman, A., Ruhl, J. E., Rykoff, E. S., Saliwanchik, B. R., Salvati, L., Sánchez, C., Sanchez, E., Cid, D. Sanchez, Saro, A., Schaffer, K. K., Secco, L. F., Sevilla-Noarbe, I., Sharon, K., Sheldon, E., Shin, T., Sievers, C., Smecher, G., Smith, M., Somboonpanyakul, T., Sommer, M., Stalder, B., Stark, A. A., Stephen, J., Strazzullo, V., Suchyta, E., Tarle, G., To, C., Troxel, M. A., Tucker, C., Tutusaus, I., Varga, T. N., Veach, T., Vieira, J. D., Vikhlinin, A., von der Linden, A., Wang, G., Weaverdyck, N., Weller, J., Whitehorn, N., Wu, W. L. K., Yanny, B., Yefremenko, V., Yin, B., Young, M., Zebrowski, J. A., Zhang, Y., Zohren, H., and Zuntz, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel'dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol ECS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range $0.25-1.78$ over a total sky area of 5,200 deg$^2$. We use DES Year 3 weak-lensing data for 688 clusters with redshifts $z<0.95$ and HST weak-lensing data for 39 clusters with $0.6
Published: 2024

22. Dark Energy Survey Deep Field photometric redshift performance and training incompleteness assessment

Author: Cipriano, L. Toribio San, De Vicente, J., Sevilla-Noarbe, I., Hartley, W. G., Myles, J., Amon, A., Bernstein, G. M., Choi, A., Eckert, K., Gruendl, R. A., Harrison, I., Sheldon, E., Yanny, B., Aguena, M., Allam, S. S., Alves, O., Bacon, D., Brooks, D., Campos, A., Rosell, A. Carnero, Carretero, J., Castander, F. J., Conselice, C., da Costa, L. N., Pereira, M. E. S., Davis, T. M., Desai, S., Diehl, H. T., Doel, P., Ferrero, I., Frieman, J., García-Bellido, J., Gaztañaga, E., Giannini, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lee, S., Lidman, C., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Palmese, A., Pieres, A., Malagón, A. A. Plazas, Roodman, A., Sanchez, E., Smith, M., Soares-Santos, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Vincenzi, M., Weaverdyck, N., and Wiseman, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: Context. The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches are machine learning techniques. These methods require a spectroscopic or reference sample to train the algorithms. Attention has to be paid to the quality and properties of these samples since they are key factors in the estimation of reliable photo-zs. Aims. The goal of this work is to calculate the photo-zs for the Y3 DES Deep Fields catalogue using the DNF machine learning algorithm. Moreover, we want to develop techniques to assess the incompleteness of the training sample and metrics to study how incompleteness affects the quality of photometric redshifts. Finally, we are interested in comparing the performance obtained with respect to the EAzY template fitting approach on Y3 DES Deep Fields catalogue. Methods. We have emulated -- at brighter magnitude -- the training incompleteness with a spectroscopic sample whose redshifts are known to have a measurable view of the problem. We have used a principal component analysis to graphically assess incompleteness and to relate it with the performance parameters provided by DNF. Finally, we have applied the results about the incompleteness to the photo-z computation on Y3 DES Deep Fields with DNF and estimated its performance. Results. The photo-zs for the galaxies on DES Deep Fields have been computed with the DNF algorithm and added to the Y3 DES Deep Fields catalogue. They are available at https://des.ncsa.illinois.edu/releases/y3a2/Y3deepfields. Some techniques have been developed to evaluate the performance in the absence of "true" redshift and to assess completeness. We have studied... (Partial abstract), Comment: 14 pages, 17 figures
Published: 2023
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23. Dark Energy Survey Year 3 results: simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps I: validation on simulations

Author: Gatti, M., Jeffrey, N., Whiteway, L., Williamson, J., Jain, B., Ajani, V., Anbajagane, D., Giannini, G., Zhou, C., Porredon, A., Prat, J., Yamamoto, M., Blazek, J., Kacprzak, T., Samuroff, S., Alarcon, A., Amon, A., Bechtol, K., Becker, M., Bernstein, G., Campos, A., Chang, C., Chen, R., Choi, A., Davis, C., Derose, J., Diehl, H. T., Dodelson, S., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferte, A., Gruen, D., Gruendl, R., Harrison, I., Hartley, W. G., Herner, K., Huff, E. M., Jarvis, M., Kuropatkin, N., Leget, P. F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Raveri, M., Rollins, R. P., Roodman, A., Sanchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Aguena, M., Alves, O., Annis, J., Brooks, D., Carretero, J., Castander, F. J., Cawthon, R., da Costa, L. N., De Vicente, J., Desai, S., Ferrero, I., Flaugher, B., Friedel, D., Frieman, J., García-Bellido, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Lee, S., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Ogando, R. L. C., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Sanchez, E., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Weaverdyck, N., Weller, J., and Wiseman, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Beyond-two-point statistics contain additional information on cosmological as well as astrophysical and observational (systematics) parameters. In this methodology paper we provide an end-to-end simulation-based analysis of a set of Gaussian and non-Gaussian weak lensing statistics using detailed mock catalogues of the Dark Energy Survey. We implement: 1) second and third moments; 2) wavelet phase harmonics (WPH); 3) the scattering transform (ST). Our analysis is fully based on simulations, it spans a space of seven $\nu w$CDM cosmological parameters, and it forward models the most relevant sources of systematics of the data (masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration). We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a likelihood-free-inference approach. We validate the pipeline extensively, and we find that WPH exhibits the strongest performance when combined with second moments, followed by ST. and then by third moments. The combination of all the different statistics further enhances constraints with respect to second moments, up to 25 per cent, 15 per cent, and 90 per cent for $S_8$, $\Omega_{\rm m}$, and the Figure-Of-Merit ${\rm FoM_{S_8,\Omega_{\rm m}}}$, respectively. We further find that non-Gaussian statistics improve constraints on $w$ and on the amplitude of intrinsic alignment with respect to second moments constraints. The methodological advances presented here are suitable for application to Stage IV surveys from Euclid, Rubin-LSST, and Roman with additional validation on mock catalogues for each survey. In a companion paper we present an application to DES Year 3 data., Comment: 25 pages, 18 figures. Comments welcome!
Published: 2023

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

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

Author: Bocquet, S., Grandis, S., Bleem, L. E., Klein, M., Mohr, J. J., Aguena, M., Alarcon, A., Allam, S., Allen, S. W., Alves, O., Amon, A., Ansarinejad, B., Bacon, D., Bayliss, M., Bechtol, K., Becker, M. R., Benson, B. A., Bernstein, G. M., Brodwin, M., Brooks, D., Campos, A., Canning, R. E. A., Carlstrom, J. E., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Cawthon, R., Chang, C., Chen, R., Choi, A., Cordero, J., Costanzi, M., da Costa, L. N., Pereira, M. E. S., Davis, C., de Haan, T., DeRose, J., Desai, S., Diehl, H. T., Dodelson, S., Doel, P., Doux, C., Drlica-Wagner, A., Eckert, K., Elvin-Poole, J., Everett, S., Ferrero, I., Ferté, A., Flores, A. M., Frieman, J., García-Bellido, J., Gatti, M., Giannini, G., Gladders, M. D., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Hinton, S. R., Hollowood, D. L., Holzapfel, W. L., Honscheid, K., Huang, N., Huff, E. M., James, D. J., Jarvis, M., Kéruzoré, F., Khullar, G., Kim, K., Kraft, R., Kuehn, K., Kuropatkin, N., Lee, S., Leget, P. -F., MacCrann, N., Mahler, G., Mantz, A., Marshall, J. L., McCullough, J., McDonald, M., Mena-Fernández, J., Miquel, R., Myles, J., Navarro-Alsina, A., Ogando, R. L. C., Palmese, A., Pandey, S., Pieres, A., Malagón, A. A. Plazas, Prat, J., Raveri, M., Reichardt, C. L., Roberson, J., Rollins, R. P., Romer, A. K., Romero, C., Roodman, A., Ross, A. J., Rykoff, E. S., Salvati, L., Sánchez, C., Sanchez, E., Cid, D. Sanchez, Saro, A., Schrabback, T., Schubnell, M., Secco, L. F., Sevilla-Noarbe, I., Sharon, K., Sheldon, E., Shin, T., Smith, M., Somboonpanyakul, T., Stalder, B., Stark, A. A., Strazzullo, V., Suchyta, E., Swanson, M. E. C., Tarle, G., To, C., Troxel, M. A., Tutusaus, I., Varga, T. N., von der Linden, A., Weaverdyck, N., Weller, J., Wiseman, P., Yanny, B., Yin, B., Young, M., Zhang, Y., and Zuntz, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a Bayesian population modeling method to analyze the abundance of galaxy clusters identified by the South Pole Telescope (SPT) with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). We discuss and validate the modeling choices with a particular focus on a robust, weak-lensing-based mass calibration using DES data. For the DES Year 3 data, we report a systematic uncertainty in weak-lensing mass calibration that increases from 1% at $z=0.25$ to 10% at $z=0.95$, to which we add 2% in quadrature to account for uncertainties in the impact of baryonic effects. We implement an analysis pipeline that joins the cluster abundance likelihood with a multi-observable likelihood for the Sunyaev-Zel'dovich effect, optical richness, and weak-lensing measurements for each individual cluster. We validate that our analysis pipeline can recover unbiased cosmological constraints by analyzing mocks that closely resemble the cluster sample extracted from the SPT-SZ, SPTpol ECS, and SPTpol 500d surveys and the DES Year 3 and HST-39 weak-lensing datasets. This work represents a crucial prerequisite for the subsequent cosmological analysis of the real dataset., Comment: Accepted for publication in Phys. Rev. D. arXiv v2 corresponds to published article
Published: 2023

26. Beyond the 3rd moment: A practical study of using lensing convergence CDFs for cosmology with DES Y3

Author: Anbajagane, D., Chang, C., Banerjee, A., Abel, T., Gatti, M., Ajani, V., Alarcon, A., Amon, A., Baxter, E. J., Bechtol, K., Becker, M. R., Bernstein, G. M., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Chen, R., Choi, A., Davis, C., DeRose, J., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Elvin-Poole, J., Everett, S., Fert'e, A., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Huff, E. M., Jain, B., Jarvis, M., Jeffrey, N., Kacprzak, T., Kokron, N., Kuropatkin, N., Leget, P. -F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Rykoff, E. S., Sanchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Whiteway, L., Yanny, B., Yin, B., Zhang, Y., Abbott, T. M. C., Allam, S., Aguena, M., Alves, O., Andrade-Oliveira, F., Annis, J., Bacon, D., Blazek, J., Brooks, D., Cawthon, R., da Costa, L. N., Pereira, M. E. S., Davis, T. M., Desai, S., Doel, P., Ferrero, I., Frieman, J., Giannini, G., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Marshall, J. L., Mena-Fernandez, J., Menanteau, F., Miquel, R., Palmese, A., Pieres, A., Malag'on, A. A. Plazas, Reil, K., Sanchez, E., Smith, M., Swanson, M. E. C., Tarle, G., and Wiseman, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Widefield surveys of the sky probe many clustered scalar fields -- such as galaxy counts, lensing potential, gas pressure, etc. -- that are sensitive to different cosmological and astrophysical processes. Our ability to constrain such processes from these fields depends crucially on the statistics chosen to summarize the field. In this work, we explore the cumulative distribution function (CDF) at multiple scales as a summary of the galaxy lensing convergence field. Using a suite of N-body lightcone simulations, we show the CDFs' constraining power is modestly better than that of the 2nd and 3rd moments of the field, as they approximately capture the information from all moments of the field in a concise data vector. We then study the practical aspects of applying the CDFs to observational data, using the first three years of the Dark Energy Survey (DES Y3) data as an example, and compute the impact of different systematics on the CDFs. The contributions from the point spread function are 2-3 orders of magnitude below the cosmological signal, while those from reduced shear approximation contribute $\lesssim 1\%$ to the signal. Source clustering effects and baryon imprints contribute $1-10\%$. Enforcing scale cuts to limit systematics-driven biases in parameter constraints degrades these constraints a noticeable amount, and this degradation is similar for the CDFs and the moments. We also detect correlations between the observed convergence field and the shape noise field at $13\sigma$. We find that the non-Gaussian correlations in the noise field must be modeled accurately to use the CDFs, or other statistics sensitive to all moments, as a rigorous cosmology tool., Comment: 21 pages, 12 figures
Published: 2023

27. Detection of the significant impact of source clustering on higher-order statistics with DES Year 3 weak gravitational lensing data

Author: Gatti, M., Jeffrey, N., Whiteway, L., Ajani, V., Kacprzak, T., Zürcher, D., Chang, C., Jain, B., Blazek, J., Krause, E., Alarcon, A., Amon, A., Bechtol, K., Becker, M., Bernstein, G., Campos, A., Chen, R., Choi, A., Davis, C., Derose, J., Diehl, H. T., Dodelson, S., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferte, A., Gruen, D., Gruendl, R., Harrison, I., Hartley, W. G., Herner, K., Huff, E. M., Jarvis, M., Kuropatkin, N., Leget, P. F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Sanchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Allam, S. S., Alves, O., Aguena, M., Bacon, D., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Carretero, J., Cawthon, R., da Costa, L. N., Davis, T. M., De Vicente, J., Desai, S., Doel, P., García-Bellido, J., Giannini, G., Gutierrez, G., Ferrero, I., Frieman, J., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Marshall, J. L., Mena-Fernández, J., Miquel, R., Ogando, R. L. C., Palmese, A., Pereira, M. E. S., Malagón, A. A. Plazas, Rodriguez-Monroy, M., Samuroff, S., Sanchez, E., Schubnell, M., Smith, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Weaverdyck, N., and Wiseman, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We demonstrate and measure the impact of source galaxy clustering on higher-order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show this effect can exceed measurement uncertainties for common higher-order statistics for certain analysis choices. Source clustering effects are larger at small scales and for statistics applied to combinations of low and high redshift samples, and diminish at high redshift. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey Year 3 data we construct null tests for the source-clustering-free case, finding a $p$-value of $p=4\times10^{-3}$ (2.6 $\sigma$) using third-order map moments and $p=3\times10^{-11}$ (6.5 $\sigma$) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either be included in the model or minimized through \textit{ad-hoc} procedures (e.g. scale cuts). We verify that the procedures adopted in existing DES Y3 cosmological analyses (using map moments and peaks) were sufficient to render this effect negligible. Failing to account for source clustering can significantly impact cosmological inference from higher-order gravitational lensing statistics, e.g. higher-order N-point functions, wavelet-moment observables (including phase harmonics and scattering transforms), and deep learning or field level summary statistics of weak lensing maps. We provide recipes both to minimise the impact of source clustering and to incorporate source clustering effects into forward-modelled mock data., Comment: 5 pages, 2 figures, submitted to MNRAS Letters
Published: 2023

28. DES Y3 + KiDS-1000: Consistent cosmology combining cosmic shear surveys

Author: Survey, Dark Energy, Collaboration, Kilo-Degree Survey, Abbott, T. M. C., Aguena, M., Alarcon, A., Alves, O., Amon, A., Andrade-Oliveira, F., Asgari, M., Avila, S., Bacon, D., Bechtol, K., Becker, M. R., Bernstein, G. M., Bertin, E., Bilicki, M., Blazek, J., Bocquet, S., Brooks, D., Burger, P., Burke, D. L., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Cawthon, R., Chang, C., Chen, R., Choi, A., Conselice, C., Cordero, J., Crocce, M., da Costa, L. N., Pereira, M. E. da Silva, Dalal, R., Davis, C., de Jong, J. T. A., DeRose, J., Desai, S., Diehl, H. T., Dodelson, S., Doel, P., Doux, C., Drlica-Wagner, A., Dvornik, A., Eckert, K., Eifler, T. F., Elvin-Poole, J., Everett, S., Fang, X., Ferrero, I., Ferté, A., Flaugher, B., Friedrich, O., Frieman, J., García-Bellido, J., Gatti, M., Giannini, G., Giblin, B., Gruen, D., Gruendl, R. A., Gutierrez, G., Harrison, I., Hartley, W. G., Herner, K., Heymans, C., Hildebrandt, H., Hinton, S. R., Hoekstra, H., Hollowood, D. L., Honscheid, K., Huang, H., Huff, E. M., Huterer, D., James, D. J., Jarvis, M., Jeffrey, N., Jeltema, T., Joachimi, B., Joudaki, S., Kannawadi, A., Krause, E., Kuehn, K., Kuijken, K., Kuropatkin, N., Lahav, O., Leget, P. -F., Lemos, P., Li, S. -S., Li, X., Liddle, A. R., Lima, M., Lin, C. -A, Lin, H., MacCrann, N., Mahony, C., Marshall, J. L., McCullough, J., Mena-Fernández, J., Menanteau, F., Miquel, R., Mohr, J. J., Muir, J., Myles, J., Napolitano, N., Navarro-Alsina, A., Ogando, R. L. C., Palmese, A., Pandey, S., Park, Y., Paterno, M., Peacock, J. A., Petravick, D., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Prat, J., Radovich, M., Raveri, M., Reischke, R., Robertson, N. C., Rollins, R. P., Romer, A. K., Roodman, A., Rykoff, E. S., Samuroff, S., Sánchez, C., Sanchez, E., Sanchez, J., Schneider, P., Secco, L. F., Sevilla-Noarbe, I., Shan, H. -Y., Sheldon, E., Shin, T., Sifón, C., Smith, M., Soares-Santos, M., Stölzner, B., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., Troxel, M. A., Tröster, T., Tutusaus, I., Busch, J. L. van den, Varga, T. N., Walker, A. R., Weaverdyck, N., Wechsler, R. H., Weller, J., Wiseman, P., Wright, A. H., Yanny, B., Yin, B., Yoon, M., Zhang, Y., and Zuntz, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter $S_8 = \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$ with a mean value of $0.790^{+0.018}_{-0.014}$. The mean marginal is lower than the maximum a posteriori estimate, $S_8=0.801$, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with $S_8$ constraints from observations of the cosmic microwave background by Planck, with agreement at the $1.7\sigma$ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum., Comment: 40 pages, 21 figures, 15 tables, accepted Open Journal of Astrophysics. Download the chains from https://des.ncsa.illinois.edu/releases/y3a2/Y3key-joint-des-kids or create your own chains with CosmoSIS using https://github.com/joezuntz/cosmosis-standard-library/blob/main/examples/des-y3_and_kids-1000.ini Watch the core team discuss this analysis at https://cosmologytalks.com/2023/05/26/des-kids
Published: 2023
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29. The role of mass and environment in the build up of the quenched galaxy population since cosmic noon

Author: Taylor, E., Almaini, O., Merrifield, M., Maltby, D., Wild, V., Hartley, W. G., and Rowlands, K.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We conduct the first study of how the relative quenching probability of galaxies depends on environment over the redshift range $0.5 < z < 3$, using data from the UKIDSS Ultra-Deep Survey. By constructing the stellar mass functions for quiescent and post-starburst (PSB) galaxies in high, medium and low density environments to $z = 3$, we find an excess of quenched galaxies in dense environments out to at least $z \sim 2$. Using the growth rate in the number of quenched galaxies, combined with the star-forming galaxy mass function, we calculate the probability that a given star-forming galaxy is quenched per unit time. We find a significantly higher quenching rate in dense environments (at a given stellar mass) at all redshifts. Massive galaxies (M$_* > 10^{10.7}$ M$_{\odot}$) are on average 1.7 $\pm$ 0.2 times more likely to quench per Gyr in the densest third of environments compared to the sparsest third. Finally, we compare the quiescent galaxy growth rate to the rate at which galaxies pass through a PSB phase. Assuming a visibility timescale of 500 Myr, we find that the PSB route can explain $\sim$ 50\% of the growth in the quiescent population at high stellar mass (M$_* > 10^{10.7}$ M$_{\odot}$) in the redshift range $0.5 < z < 3$, and potentially all of the growth at lower stellar masses., Comment: 12 pages, 8 figures. Accepted for publication in MNRAS
Published: 2023
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30. Combining the CLAUDS & HSC-SSP surveys: U+grizy(+YJHKs) photometry and photometric redshifts for 18M galaxies in the 20 deg2 of the HSC-SSP Deep and ultraDeep fields

Author: Desprez, G., Picouet, V., Moutard, T., Arnouts, S., Sawicki, M., Coupon, J., Gwyn, S., Chen, L., Huang, J., Golob, A., Furusawa, H., Ikeda, H., Paltani, S., Cheng, C., Hartley, W., Hsieh, B. C., Ilbert, O., Kauffmann, O. B., McCracken, H. J., Shuntov, M., Tanaka, M., Toft, S., Tresse, L., and Weaver, J. R.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We present the combination of the Canada-France-Hawaii Telescope (CHFT) Large Area $U$-bands Deep Survey (CLAUDS) and the Hyper-Suprime-Cam (HSC) Subaru Strategic Program (HSC-SSP) data over their four deep fields. We provide photometric catalogs for $u$, $u^*$ (CFHT--MegaCam), $g$, $r$, $i$, $z$, and $y$ (Subaru--HSC) bands over $\sim 20~{\rm deg}^2$, complemented in two fields by data from the Visible and Infrared Survey Telescope for Astronomy (VISTA) Deep Extragalactic Observations (VIDEO) survey and the UltraVISTA survey, thus extending the wavelength coverage toward near-infrared with VIRCAM $Y$, $J$, $H$, and $K_s$ observations over $5.5~{\rm deg}^2$. The extraction of the photometry was performed with two different softwares: the HSC pipeline hscPipe and the standard and robust SExtractor software. Photometric redshifts were computed with template-fitting methods using the new Phosphoros code for the hscPipe photometry and the well-known Le Phare code for the SExtractor photometry. The products of these methods were compared with each other in detail. We assessed their quality using the large spectroscopic sample available in those regions, together with photometry and photometric redshifts from COSMOS2020, the latest version of the Cosmic Evolution Survey catalogs. We find that both photometric data sets are in good agreement in $Ugrizy$ down to magnitude$\sim26$, and to magnitude$\sim24.5$ in the $YJHK_s$ bands. We achieve good performance for the photometric redshifts, reaching precisions of $\sigma_{NMAD} \lesssim 0.04$ down to ${m}_i\sim25$, even using only the CLAUDS and HSC bands. At the same magnitude limit, we measured an outlier fraction of $\eta \lesssim 10\%$ when using the $Ugrizy$ bands, and down to $\eta \lesssim 6\%$ when considering near-infrared data. [abridged], Comment: 25 pages (20+5 Appendices), 17 figures (+4 in appendices), 4 Tables (+2 in appendices), Accepted for publication in A&A
Published: 2023
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31. Non-local contribution from small scales in galaxy-galaxy lensing: Comparison of mitigation schemes

Author: Prat, J., Zacharegkas, G., Park, Y., MacCrann, N., Switzer, E. R., Pandey, S., Chang, C., Blazek, J., Miquel, R., Alarcon, A., Alves, O., Amon, A., Andrade-Oliveira, F., Bechtol, K., Becker, M. R., Bernstein, G. M., Chen, R., Choi, A., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Cordero, J., Crocce, M., Davis, C., DeRose, J., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elvin-Poole, J., Everett, S., Fang, X., Ferté, A., Fosalba, P., Friedrich, O., Gatti, M., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huang, H., Huff, E. M., Jarvis, M., Krause, E., Kuropatkin, N., Leget, P. -F., McCullough, J., Myles, J., Navarro-Alsina, A., Porredon, A., Raveri, M., Rollins, R. P., Roodman, A., Rosenfeld, R., Ross, A. J., Rykoff, E. S., Sánchez, C., Sanchez, J., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Aguena, M., Allam, S., Annis, J., Bacon, D., Bertin, E., Bocquet, S., Brooks, D., Burke, D. L., Carretero, J., Costanzi, M., Pereira, M. E. S., De Vicente, J., Desai, S., Ferrero, I., Flaugher, B., Gerdes, D. W., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Lima, M., Menanteau, F., Mena-Fernández, J., Palmese, A., Paterno, M., Paz-Chinchón, F., Pieres, A., Malagón, A. A. Plazas, Rodriguez-Monroy, M., Sanchez, E., Schubnell, M., Smith, M., Soares-Santos, M., Suchyta, E., Swanson, M. E. C., Tarle, G., To, C., Weaverdyck, N., and Weller, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Recent cosmological analyses with large-scale structure and weak lensing measurements, usually referred to as 3$\times$2pt, had to discard a lot of signal-to-noise from small scales due to our inability to accurately model non-linearities and baryonic effects. Galaxy-galaxy lensing, or the position-shear correlation between lens and source galaxies, is one of the three two-point correlation functions that are included in such analyses, usually estimated with the mean tangential shear. However, tangential shear measurements at a given angular scale $\theta$ or physical scale $R$ carry information from all scales below that, forcing the scale cuts applied in real data to be significantly larger than the scale at which theoretical uncertainties become problematic. Recently there have been a few independent efforts that aim to mitigate the non-locality of the galaxy-galaxy lensing signal. Here we perform a comparison of the different methods, including the Y-transformation, the Point-Mass marginalization methodology and the Annular Differential Surface Density statistic. We do the comparison at the cosmological constraints level in a combined galaxy clustering and galaxy-galaxy lensing analysis. We find that all the estimators yield equivalent cosmological results assuming a simulated Rubin Observatory Legacy Survey of Space and Time (LSST) Year 1 like setup and also when applied to DES Y3 data. With the LSST Y1 setup, we find that the mitigation schemes yield $\sim$1.3 times more constraining $S_8$ results than applying larger scale cuts without using any mitigation scheme., Comment: 11+4 pages, 4+4 figures. Matches the accepted version in MNRAS
Published: 2022
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32. Using the SourceXtractor++ package for data reduction

Author: Kümmel, M., Álvarez-Ayllón, A., Bertin, E., Dubath, P., Gavazzi, R., Hartley, W., and Schefer, M.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The Euclid satellite is an ESA mission scheduled for launch in September 2023. To optimally perform critical stages of the data reduction, such as object detection and morphology determination, a new and modern software package was required. We have developed SourceXtractor++ as open source software for detecting and measuring sources in astronomical images. It is a complete redesign of the original SExtractor, written mainly in C++. The package follows a modular approach and facilitates the analysis of multiple overlapping sources over many images with different pixel grids. SourceXtractor++ is already operational in many areas of the Euclid processing, and we demonstrate here the capabilities of the current version v0.19 on the basis of a set of typical use cases, which are available for download, Comment: 4 pages, 2 figures
Published: 2022

33. The Dark Energy Survey Year 3 high redshift sample: Selection, characterization and analysis of galaxy clustering

Author: Sánchez, C., Alarcon, A., Bernstein, G. M., Sanchez, J., Pandey, S., Raveri, M., Prat, J., Weaverdyck, N., Sevilla-Noarbe, I., Chang, C., Baxter, E., Omori, Y., Jain, B., Alves, O., Amon, A., Bechtol, K., Becker, M. R., Blazek, J., Choi, A., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Crocce, M., Cross, D., DeRose, J., Diehl, H. T., Dodelson, S., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elvin-Poole, J., Everett, S., Fang, X., Fosalba, P., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Huang, H., Huff, E. M., Kuropatkin, N., MacCrann, N., McCullough, J., Myles, J., Krause, E., Porredon, A., Rodriguez-Monroy, M., Rykoff, E. S., Secco, L. F., Sheldon, E., Troxel, M. A., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Abbott, T. M. C., Aguena, M., Allam, S., Andrade-Oliveira, F., Bertin, E., Bocquet, S., Brooks, D., Burke, D. L., Carretero, J., Castander, F. J., Cawthon, R., Conselice, C., Costanzi, M., Pereira, M. E. S., Desai, S., Doel, P., Doux, C., Ferrero, I., Flaugher, B., Frieman, J., García-Bellido, J., Gutierrez, G., Herner, K., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Ogando, R. L. C., Palmese, A., Paz-Chinchón, F., Pieres, A., Malagón, A. A. Plazas, Sanchez, E., Scarpine, V., Schubnell, M., Smith, M., Suchyta, E., Tarle, G., Thomas, D., and To, C.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The fiducial cosmological analyses of imaging galaxy surveys like the Dark Energy Survey (DES) typically probe the Universe at redshifts $z < 1$. This is mainly because of the limited depth of these surveys, and also because such analyses rely heavily on galaxy lensing, which is more efficient at low redshifts. In this work we present the selection and characterization of high-redshift galaxy samples using DES Year 3 data, and the analysis of their galaxy clustering measurements. In particular, we use galaxies that are fainter than those used in the previous DES Year 3 analyses and a Bayesian redshift scheme to define three tomographic bins with mean redshifts around $z \sim 0.9$, $1.2$ and $1.5$, which significantly extend the redshift coverage of the fiducial DES Year 3 analysis. These samples contain a total of about 9 million galaxies, and their galaxy density is more than 2 times higher than those in the DES Year 3 fiducial case. We characterize the redshift uncertainties of the samples, including the usage of various spectroscopic and high-quality redshift samples, and we develop a machine-learning method to correct for correlations between galaxy density and survey observing conditions. The analysis of galaxy clustering measurements, with a total signal-to-noise $S/N \sim 70$ after scale cuts, yields robust cosmological constraints on a combination of the fraction of matter in the Universe $\Omega_m$ and the Hubble parameter $h$, $\Omega_m h = 0.195^{+0.023}_{-0.018}$, and 2-3% measurements of the amplitude of the galaxy clustering signals, probing galaxy bias and the amplitude of matter fluctuations, $b \sigma_8$. A companion paper $\textit{(in preparation)}$ will present the cross-correlations of these high-$z$ samples with CMB lensing from Planck and SPT, and the cosmological analysis of those measurements in combination with the galaxy clustering presented in this work., Comment: 28 pages, 25 figures. To be submitted to MNRAS. Comments welcome
Published: 2022

34. Mapping Variations of Redshift Distributions with Probability Integral Transforms

Author: Myles, J., Gruen, D., Amon, A., Alarcon, A., DeRose, J., Everett, S., Dodelson, S., Bernstein, G. M., Campos, A., Harrison, I., MacCrann, N., McCullough, J., Raveri, M., Sánchez, C., Troxel, M. A., Yin, B., Abbott, T. M. C., Allam, S., Alves, O., Andrade-Oliveira, F., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Cawthon, R., Costanzi, M., da Costa, L. N., Pereira, M. E. S., Desai, S., Doel, P., Ferrero, I., Flaugher, B., Frieman, J., García-Bellido, J., Gatti, M., Gerdes, D. W., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hartley, W. G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Melchior, P., Mena-Fernández, J., Menanteau, F., Miquel, R., Mohr, J. J., Palmese, A., Paz-Chinchón, F., Pieres, A., Malagón, A. A. Plazas, Prat, J., Rodriguez-Monroy, M., Sanchez, E., Scarpine, V., Sevilla-Noarbe, I., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Tucker, D. L., Vincenzi, M., and Weaverdyck, N.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a method for mapping variations between probability distribution functions and apply this method within the context of measuring galaxy redshift distributions from imaging survey data. This method, which we name PITPZ for the probability integral transformations it relies on, uses a difference in curves between distribution functions in an ensemble as a transformation to apply to another distribution function, thus transferring the variation in the ensemble to the latter distribution function. This procedure is broadly applicable to the problem of uncertainty propagation. In the context of redshift distributions, for example, the uncertainty contribution due to certain effects can be studied effectively only in simulations, thus necessitating a transfer of variation measured in simulations to the redshift distributions measured from data. We illustrate the use of PITPZ by using the method to propagate photometric calibration uncertainty to redshift distributions of the Dark Energy Survey Year 3 weak lensing source galaxies. For this test case, we find that PITPZ yields a lensing amplitude uncertainty estimate due to photometric calibration error within 1 per cent of the truth, compared to as much as a 30 per cent underestimate when using traditional methods.
Published: 2022
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35. Euclid preparation XXVI. The Euclid Morphology Challenge. Towards structural parameters for billions of galaxies

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

Author: Euclid Collaboration, Merlin, E., Castellano, M., Bretonnière, H., Huertas-Company, M., Kuchner, U., Tuccillo, D., Buitrago, F., Peterson, J. R., Conselice, C. J., Caro, F., Dimauro, P., Nemani, L., Fontana, A., Kümmel, M., Häußler, B., Hartley, W. G., Ayllon, A. Alvarez, Bertin, E., Dubath, P., Ferrari, F., Ferreira, L., Gavazzi, R., Hernández-Lang, D., Lucatelli, G., Robotham, A. S. G., Schefer, M., Tortora, C., Aghanim, N., Amara, A., Amendola, L., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Kermiche, S., Kiessling, A., Kitching, T., Kohley, R., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., McCracken, H. J, Medinaceli, E., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Polenta, G., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Skottfelt, J., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Boucaud, A., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Lindholm, V., Mauri, N., Mei, S., Neissner, C., Scottez, V., Tramacere, A., Zucca, E., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Bernardeau, F., Biviano, A., Borgani, S., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Cooray, A. R., Coupon, J., Courtois, H. M., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Escartin, J. A., Escoffier, S., Farina, M., Ganga, K., Garcia-Bellido, J., George, K., Gozaliasl, G., Hildebrandt, H., Hook, I., Ilbert, O., Ilic, S., Joachimi, B., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Mainetti, G., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Matthew, S., Maturi, M., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Schirmer, M., Sereno, M., Stadel, J., Teyssier, R., Valieri, C., Valiviita, J., van Mierlo, S. E., Veropalumbo, A., Viel, M., Weaver, J. R., and Scott, D.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The ESA Euclid mission will provide high-quality imaging for about 1.5 billion galaxies. A software pipeline to automatically process and analyse such a huge amount of data in real time is being developed by the Science Ground Segment of the Euclid Consortium; this pipeline will include a model-fitting algorithm, which will provide photometric and morphological estimates of paramount importance for the core science goals of the mission and for legacy science. The Euclid Morphology Challenge is a comparative investigation of the performance of five model-fitting software packages on simulated Euclid data, aimed at providing the baseline to identify the best suited algorithm to be implemented in the pipeline. In this paper we describe the simulated data set, and we discuss the photometry results. A companion paper (Euclid Collaboration: Bretonni\`ere et al. 2022) is focused on the structural and morphological estimates. We created mock Euclid images simulating five fields of view of 0.48 deg2 each in the $I_E$ band of the VIS instrument, each with three realisations of galaxy profiles (single and double S\'ersic, and 'realistic' profiles obtained with a neural network); for one of the fields in the double S\'ersic realisation, we also simulated images for the three near-infrared $Y_E$, $J_E$ and $H_E$ bands of the NISP-P instrument, and five Rubin/LSST optical complementary bands ($u$, $g$, $r$, $i$, and $z$). To analyse the results we created diagnostic plots and defined ad-hoc metrics. Five model-fitting software packages (DeepLeGATo, Galapagos-2, Morfometryka, ProFit, and SourceXtractor++) were compared, all typically providing good results. (cut), Comment: 29 pages, 33 figures. Euclid pre-launch key paper. Companion paper: Bretonniere et al. 2022
Published: 2022
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37. Dark Energy Survey Year 3 results: Magnification modeling and impact on cosmological constraints from galaxy clustering and galaxy-galaxy lensing

Author: Elvin-Poole, J., MacCrann, N., Everett, S., Prat, J., Rykoff, E. S., De Vicente, J., Yanny, B., Herner, K., Ferté, A., Di Valentino, E., Choi, A., Burke, D. L., Sevilla-Noarbe, I., Alarcon, A., Alves, O., Amon, A., Andrade-Oliveira, F., Baxter, E., Bechtol, K., Becker, M. R., Bernstein, G. M., Blazek, J., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Cordero, J., Crocce, M., Davis, C., DeRose, J., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elsner, F., Fang, X., Fosalba, P., Friedrich, O., Gatti, M., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Huang, H., Huff, E. M., Huterer, D., Krause, E., Kuropatkin, N., Leget, P. -F., Lemos, P., Liddle, A. R., McCullough, J., Muir, J., Myles, J., Navarro-Alsina, A., Pandey, S., Park, Y., Porredon, A., Raveri, M., Rodriguez-Monroy, M., Rollins, R. P., Roodman, A., Rosenfeld, R., Ross, A. J., Sánchez, C., Sanchez, J., Secco, L. F., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Weaverdyck, N., Wechsler, R. H., Yin, B., Zhang, Y., Zuntz, J., Aguena, M., Avila, S., Bacon, D., Bertin, E., Bocquet, S., Brooks, D., García-Bellido, J., Honscheid, K., Jarvis, M., Li, T. S., Mena-Fernández, J., To, C., and Wilkinson, R. D.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We study the effect of magnification in the Dark Energy Survey Year 3 analysis of galaxy clustering and galaxy-galaxy lensing, using two different lens samples: a sample of Luminous red galaxies, redMaGiC, and a sample with a redshift-dependent magnitude limit, MagLim. We account for the effect of magnification on both the flux and size selection of galaxies, accounting for systematic effects using the Balrog image simulations. We estimate the impact of magnification on the galaxy clustering and galaxy-galaxy lensing cosmology analysis, finding it to be a significant systematic for the MagLim sample. We show cosmological constraints from the galaxy clustering auto-correlation and galaxy-galaxy lensing signal with different magnifications priors, finding broad consistency in cosmological parameters in $\Lambda$CDM and $w$CDM. However, when magnification bias amplitude is allowed to be free, we find the two-point correlations functions prefer a different amplitude to the fiducial input derived from the image simulations. We validate the magnification analysis by comparing the cross-clustering between lens bins with the prediction from the baseline analysis, which uses only the auto-correlation of the lens bins, indicating systematics other than magnification may be the cause of the discrepancy. We show adding the cross-clustering between lens redshift bins to the fit significantly improves the constraints on lens magnification parameters and allows uninformative priors to be used on magnification coefficients, without any loss of constraining power or prior volume concerns., Comment: Version accepted for publication in MNRAS. 21 pages, 13 figures, See this https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/ URL for the full DES Y3 cosmology release
Published: 2022
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38. Dark Energy Survey Year 3 Results: Redshift Calibration of the MagLim Lens Sample from the combination of SOMPZ and clustering and its impact on Cosmology

Author: Giannini, G., Alarcon, A., Gatti, M., Porredon, A., Crocce, M., Bernstein, G. M., Cawthon, R., Sánchez, C., Doux, C., Elvin-Poole, J., Raveri, M., Myles, J., Amon, A., Allam, S., Alves, O., Andrade-Oliveira, F., Baxter, E., Bechtol, K., Becker, M. R., Blazek, J., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Choi, A., Cordero, J., De Vicente, J., DeRose, J., Diehl, H. T., Dodelson, S., Drlica-Wagner, A., Eckert, K., Everett, S., Fang, X., Farahi, A., Fosalba, P., Friedrich, O., Gruen, D., Gruendl, R. A., Gschwend, J., Harrison, I., Hartley, W. G., Huff, E. M., Jarvis, M., Krause, E., Kuropatkin, N., Lemos, P., MacCrann, N., McCullough, J., Muir, J., Pandey, S., Prat, J., Rodriguez-Monroy, M., Ross, A. J., Rykoff, E. S., Samuroff, S., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Troxel, M. A., Tucker, D. L., Weaverdyck, N., Yanny, B., Yin, B., Zhang, Y., Abbott, T. M. C., Aguena, M., Bacon, D., Bertin, E., Bocquet, S., Brooks, D., Burke, D. L., Carretero, J., Castander, F. J., Costanzi, M., da Costa, L. N., Pereira, M. E. S., Desai, S., Doel, P., Ferrero, I., Flaugher, B., Friedel, D., Frieman, J., García-Bellido, J., Gerdes, D. W., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kent, S., Kuehn, K., Lahav, O., Lidman, C., Lima, M., Melchior, P., Mena-Fernández, J., Menanteau, F., Miquel, R., Ogando, R. L. C., Paterno, M., Paz-Chinchón, F., Pieres, A., Malagón, A. A. Plazas, Roodman, A., Sanchez, E., Scarpine, V., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., and Vincenzi, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present an alternative calibration of the MagLim lens sample redshift distributions from the Dark Energy Survey (DES) first three years of data (Y3). The new calibration is based on a combination of a Self-Organising Maps based scheme and clustering redshifts to estimate redshift distributions and inherent uncertainties, which is expected to be more accurate than the original DES Y3 redshift calibration of the lens sample. We describe in detail the methodology, we validate it on simulations and discuss the main effects dominating our error budget. The new calibration is in fair agreement with the fiducial DES Y3 redshift distributions calibration, with only mild differences ($<3\sigma$) in the means and widths of the distributions. We study the impact of this new calibration on cosmological constraints, analysing DES Y3 galaxy clustering and galaxy-galaxy lensing measurements, assuming a $\Lambda$CDM cosmology. We obtain $\Omega_{\rm m} = 0.30\pm 0.04$, $\sigma_8 = 0.81\pm 0.07 $ and $S_8 = 0.81\pm 0.04$, which implies a $\sim 0.4\sigma$ shift in the $\Omega_{\rm}-S_8$ plane compared to the fiducial DES Y3 results, highlighting the importance of the redshift calibration of the lens sample in multi-probe cosmological analyses.
Published: 2022
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39. Dark Energy Survey Year 3 Results: Constraints on extensions to $\Lambda$CDM with weak lensing and galaxy clustering

Author: DES Collaboration, Abbott, T. M. C., Aguena, M., Alarcon, A., Alves, O., Amon, A., Annis, J., Avila, S., Bacon, D., Baxter, E., Bechtol, K., Becker, M. R., Bernstein, G. M., Birrer, S., Blazek, J., Bocquet, S., Brandao-Souza, A., Bridle, S. L., Brooks, D., Burke, D. L., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Cawthon, R., Chang, C., Chen, A., Chen, R., Choi, A., Conselice, C., Cordero, J., Costanzi, M., Crocce, M., da Costa, L. N., Pereira, M. E. S., Davis, C., Davis, T. M., DeRose, J., Desai, S., Di Valentino, E., Diehl, H. T., Dodelson, S., Doel, P., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elsner, F., Elvin-Poole, J., Everett, S., Fang, X., Farahi, A., Ferrero, I., Ferté, A., Flaugher, B., Fosalba, P., Friedel, D., Friedrich, O., Frieman, J., García-Bellido, J., Gatti, M., Giani, L., Giannantonio, T., Giannini, G., Gruen, D., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hamaus, N., Harrison, I., Hartley, W. G., Herner, K., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huang, H., Huff, E. M., Huterer, D., Jain, B., James, D. J., Jarvis, M., Jeffrey, N., Jeltema, T., Kovacs, A., Krause, E., Kuehn, K., Kuropatkin, N., Lahav, O., Lee, S., Leget, P. -F., Lemos, P., Leonard, C. D., Liddle, A. R., Lima, M., Lin, H., MacCrann, N., Marshall, J. L., McCullough, J., Mena-Fernández, J., Menanteau, F., Miquel, R., Miranda, V., Mohr, J. J., Muir, J., Myles, J., Nadathur, S., Navarro-Alsina, A., Nichol, R. C., Ogando, R. L. C., Omori, Y., Palmese, A., Pandey, S., Park, Y., Paterno, M., Paz-Chinchón, F., Percival, W. J., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Prat, J., Raveri, M., Rodriguez-Monroy, M., Rogozenski, P., Rollins, R. P., Romer, A. K., Roodman, A., Rosenfeld, R., Ross, A. J., Rykoff, E. S., Samuroff, S., Sánchez, C., Sanchez, E., Sanchez, J., Cid, D. Sanchez, Scarpine, V., Scolnic, D., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Smith, M., Soares-Santos, M., Suchyta, E., Tabbutt, M., Tarle, G., Thomas, D., To, C., Troja, A., Troxel, M. A., Tutusaus, I., Varga, T. N., Vincenzi, M., Walker, A. R., Weaverdyck, N., Wechsler, R. H., Weller, J., Yanny, B., Yin, B., Zhang, Y., and Zuntz, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We constrain extensions to the $\Lambda$CDM model using measurements from the Dark Energy Survey's first three years of observations and external data. The DES data are the two-point correlation functions of weak gravitational lensing, galaxy clustering, and their cross-correlation. We use simulated data and blind analyses of real data to validate the robustness of our results. In many cases, constraining power is limited by the absence of nonlinear predictions that are reliable at our required precision. The models are: dark energy with a time-dependent equation of state, non-zero spatial curvature, sterile neutrinos, modifications of gravitational physics, and a binned $\sigma_8(z)$ model which serves as a probe of structure growth. For the time-varying dark energy equation of state evaluated at the pivot redshift we find $(w_{\rm p}, w_a)= (-0.99^{+0.28}_{-0.17},-0.9\pm 1.2)$ at 68% confidence with $z_{\rm p}=0.24$ from the DES measurements alone, and $(w_{\rm p}, w_a)= (-1.03^{+0.04}_{-0.03},-0.4^{+0.4}_{-0.3})$ with $z_{\rm p}=0.21$ for the combination of all data considered. Curvature constraints of $\Omega_k=0.0009\pm 0.0017$ and effective relativistic species $N_{\rm eff}=3.10^{+0.15}_{-0.16}$ are dominated by external data. For massive sterile neutrinos, we improve the upper bound on the mass $m_{\rm eff}$ by a factor of three compared to previous analyses, giving 95% limits of $(\Delta N_{\rm eff},m_{\rm eff})\leq (0.28, 0.20\, {\rm eV})$. We also constrain changes to the lensing and Poisson equations controlled by functions $\Sigma(k,z) = \Sigma_0 \Omega_{\Lambda}(z)/\Omega_{\Lambda,0}$ and $\mu(k,z)=\mu_0 \Omega_{\Lambda}(z)/\Omega_{\Lambda,0}$ respectively to $\Sigma_0=0.6^{+0.4}_{-0.5}$ from DES alone and $(\Sigma_0,\mu_0)=(0.04\pm 0.05,0.08^{+0.21}_{-0.19})$ for the combination of all data. Overall, we find no significant evidence for physics beyond $\Lambda$CDM., Comment: Updated to match published version and fix a citation reference. 46 pages, 25 figures, data available at https://dev.des.ncsa.illinois.edu/releases/y3a2/Y3key-extensions
Published: 2022
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40. Constraining the Baryonic Feedback with Cosmic Shear Using the DES Year-3 Small-Scale Measurements

Author: Chen, A., Aricò, G., Huterer, D., Angulo, R., Weaverdyck, N., Friedrich, O., Secco, L. F., Hernández-Monteagudo, C., Alarcon, A., Alves, O., Amon, A., Andrade-Oliveira, F., Baxter, E., Bechtol, K., Becker, M. R., Bernstein, G. M., Blazek, J., Brandao-Souza, A., Bridle, S. L., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Chintalapati, P., Choi, A., Cordero, J., Crocce, M., Pereira, M. E. S., Davis, C., DeRose, J., Di Valentino, E., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elsner, F., Elvin-Poole, J., Everett, S., Fang, X., Ferté, A., Fosalba, P., Gatti, M., Gaztanaga, E., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Hoffmann, K., Huang, H., Huff, E. M., Jain, B., Jarvis, M., Jeffrey, N., Kacprzak, T., Krause, E., Kuropatkin, N., Leget, P. -F., Lemos, P., Liddle, A. R., MacCrann, N., McCullough, J., Muir, J., Myles, J., Navarro-Alsina, A., Omori, Y., Pandey, S., Park, Y., Porredon, A., Prat, J., Raveri, M., Refregier, A., Rollins, R. P., Roodman, A., Rosenfeld, R., Ross, A. J., Rykoff, E. S., Samuroff, S., Sánchez, C., Sanchez, J., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troja, A., Troxel, M. A., Tutusaus, I., Varga, T. N., Wechsler, R. H., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Aguena, M., Annis, J., Bacon, D., Bertin, E., Bocquet, S., Brooks, D., Burke, D. L., Carretero, J., Conselice, C., Costanzi, M., da Costa, L. N., De Vicente, J., Desai, S., Doel, P., Ferrero, I., Flaugher, B., Frieman, J., García-Bellido, J., Gerdes, D. W., Giannantonio, T., Gschwend, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., March, M., Marshall, J. L., Melchior, P., Menanteau, F., Miquel, R., Mohr, J. J., Morgan, R., Paz-Chinchón, F., Pieres, A., Sanchez, E., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., and To, C.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We use the small scales of the Dark Energy Survey (DES) Year-3 cosmic shear measurements, which are excluded from the DES Year-3 cosmological analysis, to constrain the baryonic feedback. To model the baryonic feedback, we adopt a baryonic correction model and use the numerical package \texttt{Baccoemu} to accelerate the evaluation of the baryonic nonlinear matter power spectrum. We design our analysis pipeline to focus on the constraints of the baryonic suppression effects, utilizing the implication given by a principal component analysis on the Fisher forecasts. Our constraint on the baryonic effects can then be used to better model and ameliorate the effects of baryons in producing cosmological constraints from the next generation large-scale structure surveys. We detect the baryonic suppression on the cosmic shear measurements with a $\sim 2 \sigma$ significance. The characteristic halo mass for which half of the gas is ejected by baryonic feedback is constrained to be $M_c > 10^{13.2} h^{-1} M_{\odot}$ (95\% C.L.). The best-fit baryonic suppression is $\sim 5\%$ at $k=1.0 {\rm Mpc}\ h^{-1}$ and $\sim 15\%$ at $k=5.0 {\rm Mpc} \ h^{-1}$. Our findings are robust with respect to the assumptions about the cosmological parameters, specifics of the baryonic model, and intrinsic alignments., Comment: 20 pages, 10 figures. DES Collaboration, Year-3 analysis
Published: 2022
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41. DeepZipper II: Searching for Lensed Supernovae in Dark Energy Survey Data with Deep Learning

Author: Morgan, Robert, Nord, B., Bechtol, K., Möller, A., Hartley, W. G., Birrer, S., González, S. J., Martinez, M., Gruendl, R. A., Buckley-Geer, E. J., Shajib, A. J., Rosell, A. Carnero, Lidman, C., Collett, T., Abbott, T. M. C., Aguena, M., Andrade-Oliveira, F., Annis, J., Bacon, D., Bocquet, S., Brooks, D., Burke, D. L., Kind, M. Carrasco, Carretero, J., Castander, F. J., Conselice, C., da Costa, L. N., Costanzi, M., De Vicente, J., Desai, S., Doel, P., Everett, S., Ferrero, I., Flaugher, B., Friedel, D., Frieman, J., García-Bellido, J., Gaztanaga, E., Gruen, D., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., Menanteau, F., Miquel, R., Palmese, A., Paz-Chinchón, F., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Prat, J., Rodriguez-Monroy, M., Romer, A. K., Roodman, A., Sanchez, E., Scarpine, V., Sevilla-Noarbe, I., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., and Varga, T. N.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Gravitationally lensed supernovae (LSNe) are important probes of cosmic expansion, but they remain rare and difficult to find. Current cosmic surveys likely contain and 5-10 LSNe in total while next-generation experiments are expected to contain several hundreds to a few thousands of these systems. We search for these systems in observed Dark Energy Survey (DES) 5-year SN fields -- 10 3-sq. deg. regions of sky imaged in the $griz$ bands approximately every six nights over five years. To perform the search, we utilize the DeepZipper approach: a multi-branch deep learning architecture trained on image-level simulations of LSNe that simultaneously learns spatial and temporal relationships from time series of images. We find that our method obtains a LSN recall of 61.13% and a false positive rate of 0.02% on the DES SN field data. DeepZipper selected 2,245 candidates from a magnitude-limited ($m_i$ $<$ 22.5) catalog of 3,459,186 systems. We employ human visual inspection to review systems selected by the network and find three candidate LSNe in the DES SN fields., Comment: Accepted by ApJ
Published: 2022
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42. The DECam Local Volume Exploration Survey Data Release 2

Author: Drlica-Wagner, A., Ferguson, P. S., Adamów, M., Aguena, M., Andrade-Oliveira, F., Bacon, D., Bechtol, K., Bell, E. F., Bertin, E., Bilaji, P., Bocquet, S., Bom, C. R., Brooks, D., Burke, D. L., Carballo-Bello, J. A., Carlin, J. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Cerny, W., Chang, C., Choi, Y., Conselice, C., Costanzi, M., Crnojević, D., da Costa, L. N., De Vicente, J., Desai, S., Esteves, J., Everett, S., Ferrero, I., Fitzpatrick, M., Flaugher, B., Friedel, D., Frieman, J., García-Bellido, J., Gatti, M., Gaztanaga, E., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gschwend, J., Hartley, W. G., Hernandez-Lang, D., Hinton, S. R., Hollowood, D. L., Honscheid, K., Hughes, A. K., Jacques, A., James, D. J., Johnson, M. D., Kuehn, K., Kuropatkin, N., Lahav, O., Li, T. S., Lidman, C., Lin, H., March, M., Marshall, J. L., Martínez-Delgado, D., Martínez-Vázquez, C. E., Massana, P., Mau, S., McNanna, M., Melchior, P., Menanteau, F., Miller, A. E., Miquel, R., Mohr, J. J., Morgan, R., Mutlu-Pakdil, B., Muñoz, R. R., Neilsen, E. H., Nidever, D. L., Nikutta, R., Castellon, J. L. Nilo, Noël, N. E. D., Ogando, R. L. C., Olsen, K. A. G., Pace, A. B., Palmese, A., Paz-Chinchón, F., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Prat, J., Riley, A. H., Rodriguez-Monroy, M., Romer, A. K., Roodman, A., Sako, M., Sakowska, J. D., Sanchez, E., Sánchez, F. J., Sand, D. J., Santana-Silva, L., Santiago, B., Schubnell, M., Serrano, S., Sevilla-Noarbe, I., Simon, J. D., Smith, M., Soares-Santos, M., Stringfellow, G. S., Suchyta, E., Suson, D. J., Tan, C. Y., Tarle, G., Tavangar, K., Thomas, D., To, C., Tollerud, E. J., Troxel, M. A., Tucker, D. L., Varga, T. N., Vivas, A. K., Walker, A. R., Weller, J., Wilkinson, R. D., Wu, J. F., Yanny, B., Zaborowski, E., and Zenteno, A.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: We present the second public data release (DR2) from the DECam Local Volume Exploration survey (DELVE). DELVE DR2 combines new DECam observations with archival DECam data from the Dark Energy Survey, the DECam Legacy Survey, and other DECam community programs. DELVE DR2 consists of ~160,000 exposures that cover >21,000 deg^2 of the high Galactic latitude (|b| > 10 deg) sky in four broadband optical/near-infrared filters (g, r, i, z). DELVE DR2 provides point-source and automatic aperture photometry for ~2.5 billion astronomical sources with a median 5{\sigma} point-source depth of g=24.3, r=23.9, i=23.5, and z=22.8 mag. A region of ~17,000 deg^2 has been imaged in all four filters, providing four-band photometric measurements for ~618 million astronomical sources. DELVE DR2 covers more than four times the area of the previous DELVE data release and contains roughly five times as many astronomical objects. DELVE DR2 is publicly available via the NOIRLab Astro Data Lab science platform., Comment: 23 pages, 10 figures, 5 tables; to be submitted to AAS Journals; public data release at https://datalab.noirlab.edu/delve/. arXiv admin note: substantial text overlap with arXiv:2103.07476
Published: 2022
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43. Dark Energy Survey Year 3 results: cosmological constraints from the analysis of cosmic shear in harmonic space

Author: Doux, C., Jain, B., Zeurcher, D., Lee, J., Fang, X., Rosenfeld, R., Amon, A., Camacho, H., Choi, A., Secco, L. F., Blazek, J., Chang, C., Gatti, M., Gaztanaga, E., Jeffrey, N., Raveri, M., Samuroff, S., Alarcon, A., Alves, O., Andrade-Oliveira, F., Baxter, E., Bechtol, K., Becker, M. R., Bernstein, G. M., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chen, R., Cordero, J., Crocce, M., Davis, C., DeRose, J., Dodelson, S., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elsner, F., Elvin-Poole, J., Everett, S., Ferté, A., Fosalba, P., Friedrich, O., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huang, H., Huff, E. M., Huterer, D., Jarvis, M., Krause, E., Kuropatkin, N., Leget, P. -F., Lemos, P., Liddle, A. R., MacCrann, N., McCullough, J., Muir, J., Myles, J., Navarro-Alsina, A., Pandey, S., Park, Y., Porredon, A., Prat, J., Rodriguez-Monroy, M., Rollins, R. P., Roodman, A., Ross, A. J., Rykoff, E. S., Sánchez, C., Sanchez, J., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troja, A., Troxel, M. A., Tutusaus, I., Varga, T. N., Weaverdyck, N., Wechsler, R. H., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Abbott, T. M. C., Aguena, M., Allam, S., Annis, J., Bacon, D., Bertin, E., Bocquet, S., Brooks, D., Burke, D. L., Carretero, J., Costanzi, M., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Desai, S., Diehl, H. T., Doel, P., Ferrero, I., Flaugher, B., Frieman, J., García-Bellido, J., Gerdes, D. W., Giannantonio, T., Gschwend, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kim, A. G., Kuehn, K., Lahav, O., Marshall, J. L., Menanteau, F., Miquel, R., Morgan, R., Ogando, R. L. C., Palmese, A., Paz-Chinchón, F., Pieres, A., Reil, K., Sanchez, E., Scarpine, V., Serrano, S., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., and Weller, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present cosmological constraints from the analysis of angular power spectra of cosmic shear maps based on data from the first three years of observations by the Dark Energy Survey (DES Y3). Our measurements are based on the pseudo-$C_\ell$ method and offer a view complementary to that of the two-point correlation functions in real space, as the two estimators are known to compress and select Gaussian information in different ways, due to scale cuts. They may also be differently affected by systematic effects and theoretical uncertainties, such as baryons and intrinsic alignments (IA), making this analysis an important cross-check. In the context of $\Lambda$CDM, and using the same fiducial model as in the DES Y3 real space analysis, we find ${S_8 \equiv \sigma_8 \sqrt{\Omega_{\rm m}/0.3} = 0.793^{+0.038}_{-0.025}}$, which further improves to ${S_8 = 0.784\pm 0.026 }$ when including shear ratios. This constraint is within expected statistical fluctuations from the real space analysis, and in agreement with DES~Y3 analyses of non-Gaussian statistics, but favors a slightly higher value of $S_8$, which reduces the tension with the Planck cosmic microwave background 2018 results from $2.3\sigma$ in the real space analysis to $1.5\sigma$ in this work. We explore less conservative IA models than the one adopted in our fiducial analysis, finding no clear preference for a more complex model. We also include small scales, using an increased Fourier mode cut-off up to $k_{\rm max}={5}{h{\rm Mpc}^{-1}}$, which allows to constrain baryonic feedback while leaving cosmological constraints essentially unchanged. Finally, we present an approximate reconstruction of the linear matter power spectrum at present time, which is found to be about 20\% lower than predicted by Planck 2018, as reflected by the $1.5\sigma$ lower $S_8$ value.
Published: 2022
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44. Robust sampling for weak lensing and clustering analyses with the Dark Energy Survey

Author: Lemos, P., Weaverdyck, N., Rollins, R. P., Muir, J., Ferté, A., Liddle, A. R., Campos, A., Huterer, D., Raveri, M., Zuntz, J., Di Valentino, E., Fang, X., Hartley, W. G., Aguena, M., Allam, S., Annis, J., Bertin, E., Bocquet, S., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Choi, A., Costanzi, M., Crocce, M., da Costa, L. N., Pereira, M. E. S., Dietrich, J. P., Everett, S., Ferrero, I., Frieman, J., García-Bellido, J., Gatti, M., Gaztanaga, E., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Kuropatkin, N., Lima, M., March, M., Melchior, P., Menanteau, F., Miquel, R., Morgan, R., Palmese, A., Paz-Chinchón, F., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Sanchez, E., Scarpine, V., Schubnell, M., Serrano, S., Sevilla-Noarbe, I., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., Varga, T. N., and Weller, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Recent cosmological analyses rely on the ability to accurately sample from high-dimensional posterior distributions. A variety of algorithms have been applied in the field, but justification of the particular sampler choice and settings is often lacking. Here we investigate three such samplers to motivate and validate the algorithm and settings used for the Dark Energy Survey (DES) analyses of the first 3 years (Y3) of data from combined measurements of weak lensing and galaxy clustering. We employ the full DES Year 1 likelihood alongside a much faster approximate likelihood, which enables us to assess the outcomes from each sampler choice and demonstrate the robustness of our full results. We find that the ellipsoidal nested sampling algorithm $\texttt{MultiNest}$ reports inconsistent estimates of the Bayesian evidence and somewhat narrower parameter credible intervals than the sliced nested sampling implemented in $\texttt{PolyChord}$. We compare the findings from $\texttt{MultiNest}$ and $\texttt{PolyChord}$ with parameter inference from the Metropolis-Hastings algorithm, finding good agreement. We determine that $\texttt{PolyChord}$ provides a good balance of speed and robustness, and recommend different settings for testing purposes and final chains for analyses with DES Y3 data. Our methodology can readily be reproduced to obtain suitable sampler settings for future surveys., Comment: 16 pages, 11 figures
Published: 2022
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45. Consistent lensing and clustering in a low-$S_8$ Universe with BOSS, DES Year 3, HSC Year 1 and KiDS-1000

Author: Amon, A., Robertson, N. C., Miyatake, H., Heymans, C., White, M., DeRose, J., Yuan, S., Wechsler, R. H., Varga, T. N., Bocquet, S., Dvornik, A., More, S., Ross, A. J., Hoekstra, H., Alarcon, A., Asgari, M., Blazek, J., Campos, A., Chen, R., Choi, A., Crocce, M., Diehl, H. T., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferté, A., Gatti, M., Giannini, G., Gruen, D., Gruendl, R. A., Hartley, W. G., Herner, K., Hildebrandt, H., Huang, S., Huff, E. M., Joachimi, B., Lee, S., MacCrann, N., Myles, J., Alsina, A. Navarro, Nishimichi, T., Prat, J., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Trster, T., Troxel, M. A., Tutusaus, I., Wright, A. H., Yin, B., Aguena, M., Allam, S., Annis, J., Bacon, D., Bilicki, M., Brooks, D., Burke, D. L., Rosell, A. Carnero, Carretero, J., Castander, F. J., Cawthon, R., Costanzi, M., da Costa, L. N., Pereira, M. E. S., de Jong, J., De Vicente, J., Desai, S., Dietrich, J. P., Doel, P., Ferrero, I., Frieman, J., García-Bellido, J., Gerdes, D. W., Gschwend, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., Kannawadi, A., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., Maia, M. A. G., Marshall, J. L., Menanteau, F., Miquel, R., Mohr, J. J., Morgan, R., Muir, J., Paz-Chinchon, F., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Rodriguez-Monroy, M., Roodman, A., Sanchez, E., Serrano, S., Shan, H., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., and Zhang, Y.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We evaluate the consistency between lensing and clustering probes of large-scale structure based on measurements of projected galaxy clustering from BOSS combined with overlapping galaxy-galaxy lensing from three surveys: DES Y3, HSC Y1, and KiDS-1000. An intra-lensing-survey study finds good agreement between these lensing data. We model the observations using the Dark Emulator and fit the data at two fixed cosmologies: Planck, with $S_8=0.83$, and a Lensing cosmology with $S_8=0.76$. For a joint analysis limited to scales with $R>5.25h^{-1}$Mpc, we find that both cosmologies provide an acceptable fit to the data. Full utilisation of the small-scale clustering and lensing measurements is hindered by uncertainty in the impact of baryon feedback and assembly bias, which we account for with a reasoned theoretical error budget. We incorporate a systematic scaling parameter for each redshift bin, $A$, that decouples the lensing and clustering to capture any inconsistency. When a wide range of scales ($0.15
Published: 2022
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46. Dark Energy Survey Year 3 Results: Three-Point Shear Correlations and Mass Aperture Moments

Author: Secco, L. F., Jarvis, M., Jain, B., Chang, C., Gatti, M., Frieman, J., Adhikari, S., Alarcon, A., Amon, A., Bechtol, K., Becker, M. R., Bernstein, G. M., Blazek, J., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Choi, A., Cordero, J., DeRose, J., Dodelson, S., Doux, C., Drlica-Wagner, A., Everett, S., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Krause, E., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Prat, J., Rollins, R. P., Samuroff, S., Sanchez, C., Sevilla-Noarbe, I., Sheldon, E., Troxel, M. A., Zeurcher, D., Aguena, M., Andrade-Oliveira, F., Annis, J., Bacon, D., Bertin, E., Bocquet, S., Brooks, D., Burke, D. L., Carretero, J., Castander, F. J., Crocce, M., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Diehl, H. T., Doel, P., Eckert, K., Ferrero, I., Flaugher, B., Friedel, D., Garcia-Bellido, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., Kuehn, K., Kuropatkin, N., Maia, M. A. G., Marshall, J. L., Menanteau, F., Miquel, R., Mohr, J. J., Morgan, R., Muir, J., Paz-Chinchon, F., Pieres, A., Malagon, A. A. Plazas, Rodriguez-Monroy, M., Roodman, A., Sanchez, E., Serrano, S., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., and Weller, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present high signal-to-noise measurements of three-point shear correlations and the third moment of the mass aperture statistic using the first 3 years of data from the Dark Energy Survey. We additionally obtain the first measurements of the configuration and scale dependence of the four three-point shear correlations which carry cosmological information. With the third-order mass aperture statistic, we present tomographic measurements over angular scales of 4 to 60 arcminutes with a combined statistical significance of 15.0$\sigma$. Using the tomographic information and measuring also the second-order mass aperture, we additionally obtain a skewness parameter and its redshift evolution. We find that the amplitudes and scale-dependence of these shear 3pt functions are in qualitative agreement with measurements in a mock galaxy catalog based on N-body simulations, indicating promise for including them in future cosmological analyses. We validate our measurements by showing that B-modes, parity-violating contributions and PSF modeling uncertainties are negligible, and determine that the measured signals are likely to be of astrophysical and gravitational origin., Comment: Minor changes. Matches version published in PRD
Published: 2022
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47. The DES view of the Eridanus supervoid and the CMB Cold Spot

Author: Kovács, A., Jeffrey, N., Gatti, M., Chang, C., Whiteway, L., Hamaus, N., Lahav, O., Pollina, G., Bacon, D., Kacprzak, T., Mawdsley, B., Nadathur, S., Zeurcher, D., García-Bellido, J., Alarcon, A., Amon, A., Bechtol, K., Bernstein, G. M., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chen, R., Choi, A., Cordero, J., Davis, C., DeRose, J., Doux, C., Drlica-Wagner, A., Eckert, K., Elsner, F., Elvin-Poole, J., Everett, S., Ferté, A., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huff, E. M., Huterer, D., Kuropatkin, N., Jarvis, M., Leget, P. F., MacCrann, N., McCullough, J., Muir, J., Myles, J., Navarro-Alsina, A., Pandey, S., Prat, J., Raveri, M., Rollins, R. P., Ross, A. J., Rykoff, E. S., Sánchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Aguena, M., Allam, S., Andrade-Oliveira, F., Annis, J., Bertin, E., Brooks, D., Burke, D., Carretero, J., Costanzi, M., da Costa, L. N., Pereira, M. E. S., Davis, T., De Vicente, J., Desai, S., Diehl, H. T., Ferrero, I., Flaugher, B., Fosalba, P., Frieman, J., Gaztañaga, E., Gerdes, D., Giannantonio, T., Gschwend, J., Gutierrez, G., Hinton, S., Hollowood, D. L., Honscheid, K., James, D., Kuehn, K., Lima, M., Maia, M. A. G., Marshall, J. L., Melchior, P., Menanteau, F., Miquel, R., Morgan, R., Ogando, R., Paz-Chinchon, F., Pieres, A., Plazas, A. A., Monroy, M. Rodriguez, Romer, K., Roodman, A., Sanchez, E., Schubnell, M., Serrano, S., Smith, M., Soares-Santos, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C. -H., and Weller, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Cold Spot is a puzzling large-scale feature in the Cosmic Microwave Background temperature maps and its origin has been subject to active debate. As an important foreground structure at low redshift, the Eridanus supervoid was recently detected, but it was subsequently determined that, assuming the standard $\Lambda$CDM model, only about 10-20$\%$ of the observed temperature depression can be accounted for via its Integrated Sachs-Wolfe imprint. However, $R\gtrsim100~h^{-1}\mathrm{Mpc}$ supervoids elsewhere in the sky have shown ISW imprints $A_{\mathrm{ISW}}\approx5.2\pm1.6$ times stronger than expected from $\Lambda$CDM ($A_{\mathrm{ISW}}=1$), which warrants further inspection. Using the Year-3 redMaGiC catalogue of luminous red galaxies from the Dark Energy Survey, here we confirm the detection of the Eridanus supervoid as a significant under-density in the Cold Spot's direction at $z<0.2$. We also show, with $\mathrm{S/N}\gtrsim5$ significance, that the Eridanus supervoid appears as the most prominent large-scale under-density in the dark matter mass maps that we reconstructed from DES Year-3 gravitational lensing data. While we report no significant anomalies, an interesting aspect is that the amplitude of the lensing signal from the Eridanus supervoid at the Cold Spot centre is about $30\%$ lower than expected from similar peaks found in N-body simulations based on the standard $\Lambda$CDM model with parameters $\Omega_{\rm m} = 0.279$ and $\sigma_8 = 0.82$. Overall, our results confirm the causal relation between these individually rare structures in the cosmic web and in the CMB, motivating more detailed future surveys in the Cold Spot region., Comment: accepted for publication by MNRAS, 14 pages, 10 figures
Published: 2021
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48. Lensing Without Borders. I. A Blind Comparison of the Amplitude of Galaxy-Galaxy Lensing Between Independent Imaging Surveys

Author: Leauthaud, A., Amon, A., Singh, S., Gruen, D., Lange, J. U., Huang, S., Robertson, N. C., Varga, T. N., Luo, Y., Heymans, C., Hildebrandt, H., Blake, C., Aguena, M., Allam, S., Andrade-Oliveira, F., Annis, J., Bertin, E., Bhargava, S., Blazek, J., Bridle, S. L., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Cawthon, R., Choi, A., Costanzi, M., da Costa, L. N., Pereira, M. E. S., Davis, C., De Vicente, J., DeRose, J., Diehl, H. T., Dietrich, J. P., Doel, P., Eckert, K., Everett, S., Evrard, A. E., Ferrero, I., Flaugher, B., Fosalba, P., Garcia-Bellido, J., Gatti, M., Gaztanaga, E., Gruendl, R. A., Gschwend, J., Hartley, W. G., Hollowood, D. L., Honscheid, K., Jain, B., James, D. J., Jarvis, M., Joachimi, B., Kannawadi, A., Kim, A. G., Krause, E., Kuehn, K., Kuijken, K., Kuropatkin, N., Lima, M., MacCrann, N., Maia, M. A. G., Makler, M., March, M., Marshall, J. L., Melchior, P., Menanteau, F., Miquel, R., Miyatake, H., Mohr, J. J., Moraes, B., More, S., Surhud, M., Morgan, R., Myles, J., Ogando, R. L. C., Palmese, A., Paz-Chinchon, F., Malagon, A. A. Plazas, Prat, J., Rau, M. M., Rhodes, J., Rodriguez-Monroy, M., Roodman, A., Ross, A. J., Samuroff, S., Sanchez, C., Sanchez, E., Scarpine, V., Schlegel, D. J., Schubnell, M., Serrano, S., Sevilla-Noarbe, I., Sifon, C., Smith, M., Speagle, J. S., Suchyta, E., Tarle, G., Thomas, D., Tinker, J., To, C., Troxel, M. A., Van Waerbeke, L., Vielzeuf, P., and Wright, A. H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Lensing Without Borders is a cross-survey collaboration created to assess the consistency of galaxy-galaxy lensing signals ($\Delta\Sigma$) across different data-sets and to carry out end-to-end tests of systematic errors. We perform a blind comparison of the amplitude of $\Delta\Sigma$ using lens samples from BOSS and six independent lensing surveys. We find good agreement between empirically estimated and reported systematic errors which agree to better than 2.3$\sigma$ in four lens bins and three radial ranges. For lenses with $z_{\rm L}>0.43$ and considering statistical errors, we detect a 3-4$\sigma$ correlation between lensing amplitude and survey depth. This correlation could arise from the increasing impact at higher redshift of unrecognised galaxy blends on shear calibration and imperfections in photometric redshift calibration. At $z_{\rm L}>0.54$ amplitudes may additionally correlate with foreground stellar density. The amplitude of these trends is within survey-defined systematic error budgets which are designed to include known shear and redshift calibration uncertainty. Using a fully empirical and conservative method, we do not find evidence for large unknown systematics. Systematic errors greater than 15% (25%) ruled out in three lens bins at 68% (95%) confidence at $z<0.54$. Differences with respect to predictions based on clustering are observed to be at the 20-30% level. Our results therefore suggest that lensing systematics alone are unlikely to fully explain the "lensing is low" effect at $z<0.54$. This analysis demonstrates the power of cross-survey comparisons and provides a promising path for identifying and reducing systematics in future lensing analyses., Comment: 41 page, 20 figures
Published: 2021
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49. Cosmic Shear in Harmonic Space from the Dark Energy Survey Year 1 Data: Compatibility with Configuration Space Results

Author: Camacho, H., Andrade-Oliveira, F., Troja, A., Rosenfeld, R., Faga, L., Gomes, R., Doux, C., Fang, X., Lima, M., Miranda, V., Eifler, T. F., Friedrich, O., Gatti, M., Bernstein, G. M., Blazek, J., Bridle, S. L., Choi, A., Davis, C., DeRose, J., Gaztanaga, E., Gruen, D., Hartley, W. G., Hoyle, B., Jarvis, M., MacCrann, N., Prat, J., Rau, M. M., Samuroff, S., Sánchez, C., Sheldon, E., Troxel, M. A., Vielzeuf, P., Zuntz, J., Abbott, T. M. C., Aguena, M., Allam, S., Annis, J., Bacon, D., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Cawthon, R., Costanzi, M., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Desai, S., Diehl, H. T., Doel, P., Everett, S., Evrard, A. E., Ferrero, I., Flaugher, B., Fosalba, P., Friedel, D., Frieman, J., García-Bellido, J., Gerdes, D. W., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., James, D. J., Kuehn, K., Kuropatkin, N., Lahav, O., Maia, M. A. G., Marshall, J. L., Melchior, P., Menanteau, F., Miquel, R., Morgan, R., Paz-Chinchón, F., Petravick, D., Pieres, A., Malagón, A. A. Plazas, Reil, K., Rodriguez-Monroy, M., Sanchez, E., Scarpine, V., Schubnell, M., Serrano, S., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Suchyta, E., Tarle, G., Thomas, D., To, C., Varga, T. N., Weller, J., and Wilkinson, R. D.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We perform a cosmic shear analysis in harmonic space using the first year of data collected by the Dark Energy Survey (DES-Y1). We measure the cosmic weak lensing shear power spectra using the Metacalibration catalogue and perform a likelihood analysis within the framework of CosmoSIS. We set scale cuts based on baryonic effects contamination and model redshift and shear calibration uncertainties as well as intrinsic alignments. We adopt as fiducial covariance matrix an analytical computation accounting for the mask geometry in the Gaussian term, including non-Gaussian contributions. A suite of 1200 lognormal simulations is used to validate the harmonic space pipeline and the covariance matrix. We perform a series of stress tests to gauge the robustness of the harmonic space analysis. Finally, we use the DES-Y1 pipeline in configuration space to perform a similar likelihood analysis and compare both results, demonstrating their compatibility in estimating the cosmological parameters $S_8$, $\sigma_8$ and $\Omega_m$. The methods implemented and validated in this paper will allow us to perform a consistent harmonic space analysis in the upcoming DES data., Comment: 16 pages, 11 figures. This version matches the published one
Published: 2021
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50. Dark Energy Survey Year 3 results: Marginalisation over redshift distribution uncertainties using ranking of discrete realisations

Author: Cordero, Juan P., Harrison, Ian, Rollins, Richard P., Bernstein, G. M., Bridle, S. L., Alarcon, A., Alves, O., Amon, A., Andrade-Oliveira, F., Camacho, H., Campos, A., Choi, A., DeRose, J., Dodelson, S., Eckert, K., Eifler, T. F., Everett, S., Fang, X., Friedrich, O., Gruen, D., Gruendl, R. A., Hartley, W. G., Huff, E. M., Krause, E., Kuropatkin, N., MacCrann, N., McCullough, J., Myles, J., Pandey, S., Raveri, M., Rosenfeld, R., Rykoff, E. S., Sánchez, C., Sánchez, J., Sevilla-Noarbe, I., Sheldon, E., Troxel, M., Wechsler, R., Yanny, B., Yin, B., Zhang, Y., Aguena, M., Allam, S., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Cawthon, R., Costanzi, M., da Costa, L., Pereira, M. E. da Silva, De Vicente, J., Diehl, H. T., Dietrich, J., Doel, P., Elvin-Poole, J., Ferrero, I., Flaugher, B., Fosalba, P., Frieman, J., Garcia-Bellido, J., Gerdes, D., Gschwend, J., Gutierrez, G., Hinton, S., Hollowood, D. L., Honscheid, K., Hoyle, B., James, D., Kuehn, K., Lahav, O., Maia, M. A. G., March, M., Menanteau, F., Miquel, R., Morgan, R., Muir, J., Palmese, A., Paz-Chinchon, F., Pieres, A., Malagón, A. Plazas, Sánchez, E., Scarpine, V., Serrano, S., Smith, M., Soares-Santos, M., Suchyta, E., Swanson, M., Tarle, G., Thomas, D., To, C., and Varga, T. N.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Cosmological information from weak lensing surveys is maximised by dividing source galaxies into tomographic sub-samples for which the redshift distributions are estimated. Uncertainties on these redshift distributions must be correctly propagated into the cosmological results. We present hyperrank, a new method for marginalising over redshift distribution uncertainties in cosmological analyses, using discrete samples from the space of all possible redshift distributions. This is demonstrated in contrast to previous highly simplified parametric models of the redshift distribution uncertainty. In hyperrank the set of proposed redshift distributions is ranked according to a small (in this work between one and four) number of summary values, which are then sampled along with other nuisance parameters and cosmological parameters in the Monte Carlo chain used for inference. This can be regarded as a general method for marginalising over discrete realisations of data vector variation with nuisance parameters, which can consequently be sampled separately to the main parameters of interest, allowing for increased computational efficiency. We focus on the case of weak lensing cosmic shear analyses and demonstrate our method using simulations made for the Dark Energy Survey (DES). We show the method can correctly and efficiently marginalise over a range of models for the redshift distribution uncertainty. Finally, we compare hyperrank to the common mean-shifting method of marginalising over redshift uncertainty, validating that this simpler model is sufficient for use in the DES Year 3 cosmology results presented in companion papers., Comment: Accepted for publication in MNRAS. 17 pages, 12 figures, comments welcome Replacement: Added small comments suggested by referee
Published: 2021
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