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708 results on '"McCracken H."'

1. DEIMOS spectroscopy of z=6 protocluster candidate in COSMOS - a massive protocluster embedded in a large-scale structure?

Author: Brinch, Malte, Greve, Thomas R, Sanders, David B, Mcpartland, Conor J R, Chartab, Nima, Gillman, Steven, Vijayan, Aswin P, Lee, Minju M, Brammer, Gabriel, Casey, Caitlin M, Ilbert, Olivier, Jin, Shuowen, Magdis, Georgios, Mccracken, H J, Sillassen, Nikolaj B, Toft, Sune, Zavala, Jorge A, Brinch, Malte, Greve, Thomas R, Sanders, David B, Mcpartland, Conor J R, Chartab, Nima, Gillman, Steven, Vijayan, Aswin P, Lee, Minju M, Brammer, Gabriel, Casey, Caitlin M, Ilbert, Olivier, Jin, Shuowen, Magdis, Georgios, Mccracken, H J, Sillassen, Nikolaj B, Toft, Sune, and Zavala, Jorge A
Published: 2024

2. DEIMOS spectroscopy of z=6 protocluster candidate in COSMOS - a massive protocluster embedded in a large-scale structure?

Author: Brinch, Malte, Greve, Thomas R, Sanders, David B, Mcpartland, Conor J R, Chartab, Nima, Gillman, Steven, Vijayan, Aswin P, Lee, Minju M, Brammer, Gabriel, Casey, Caitlin M, Ilbert, Olivier, Jin, Shuowen, Magdis, Georgios, Mccracken, H J, Sillassen, Nikolaj B, Toft, Sune, Zavala, Jorge A, Brinch, Malte, Greve, Thomas R, Sanders, David B, Mcpartland, Conor J R, Chartab, Nima, Gillman, Steven, Vijayan, Aswin P, Lee, Minju M, Brammer, Gabriel, Casey, Caitlin M, Ilbert, Olivier, Jin, Shuowen, Magdis, Georgios, Mccracken, H J, Sillassen, Nikolaj B, Toft, Sune, and Zavala, Jorge A
Published: 2024

3. Mccracken, H M G, [No Service Number]

Author: Australian Red Cross Society, National Office and Australian Red Cross Society, National Office
Abstract: Surname: MCCRACKEN. Given Name(s) or Initials: H M G. Military Service Number or Last Known Location: [No Registration Number]. Missing, Wounded and Prisoner of War Enquiry Card Index Number: 16231., 223513 Item: [2016.0049.35151] "Mccracken, H M G, [No Service Number]"

4. Mccracken, H M G, [No Service Number]

Author: Australian Red Cross Society, National Office and Australian Red Cross Society, National Office
Abstract: Surname: MCCRACKEN. Given Name(s) or Initials: H M G. Military Service Number or Last Known Location: [No Registration Number]. Missing, Wounded and Prisoner of War Enquiry Card Index Number: 16231., 223513 Item: [2016.0049.35151] "Mccracken, H M G, [No Service Number]"

5. Euclid: Testing photometric selection of emission-line galaxy targets

Author: Cagliari, M. S., Granett, B. R., Guzzo, L., Bethermin, M., Bolzonella, M., de la Torre, S., Monaco, P., Moresco, M., Percival, W. J., Scarlata, C., Wang, Y., Ezziati, M., Ilbert, O., Brun, V. Le, Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moscardini, L., Munari, E., Nichol, R. C., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Scodeggio, M., Secroun, A., Seidel, G., Seiffert, M., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Surace, C., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Burigana, C., Scottez, V., Viel, M., Bisigello, L., Cagliari, M. S., Granett, B. R., Guzzo, L., Bethermin, M., Bolzonella, M., de la Torre, S., Monaco, P., Moresco, M., Percival, W. J., Scarlata, C., Wang, Y., Ezziati, M., Ilbert, O., Brun, V. Le, Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moscardini, L., Munari, E., Nichol, R. C., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Scodeggio, M., Secroun, A., Seidel, G., Seiffert, M., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Surace, C., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Weller, J., Zamorani, G., Zoubian, J., Zucca, E., Burigana, C., Scottez, V., Viel, M., and Bisigello, L.
Abstract: Multi-object spectroscopic galaxy surveys typically make use of photometric and colour criteria to select targets. Conversely, the Euclid NISP slitless spectrograph will record spectra for every source over its field of view. Slitless spectroscopy has the advantage of avoiding defining a priori a galaxy sample, but at the price of making the selection function harder to quantify. The Euclid Wide Survey aims at building robust statistical samples of emission-line galaxies with fluxes in the Halpha-NII complex brighter than 2e-16 erg/s/cm^2 and within 0.9
Published: 2024

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

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

7. Euclid preparation. The Near-IR Background Dipole Experiment with Euclid

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

8. COSMOS2020:The galaxy stellar mass function: The assembly and star formation cessation of galaxies at 0.2< z ≤ 7.5

Author: Weaver, J. R., Davidzon, I., Toft, S., Ilbert, O., McCracken, H. J., Gould, K. M.L., Jespersen, C. K., Steinhardt, C., Lagos, C. D.P., Capak, P. L., Casey, C. M., Chartab, N., Faisst, A. L., Hayward, C. C., Kartaltepe, J. S., Kauffmann, O. B., Koekemoer, A. M., Kokorev, V., Laigle, C., Liu, D., Long, A., Magdis, G. E., McPartland, C. J.R., Milvang-Jensen, B., Mobasher, B., Moneti, A., Peng, Y., Sanders, D. B., Shuntov, M., Sneppen, A., Valentino, F., Zalesky, L., Zamorani, G., Weaver, J. R., Davidzon, I., Toft, S., Ilbert, O., McCracken, H. J., Gould, K. M.L., Jespersen, C. K., Steinhardt, C., Lagos, C. D.P., Capak, P. L., Casey, C. M., Chartab, N., Faisst, A. L., Hayward, C. C., Kartaltepe, J. S., Kauffmann, O. B., Koekemoer, A. M., Kokorev, V., Laigle, C., Liu, D., Long, A., Magdis, G. E., McPartland, C. J.R., Milvang-Jensen, B., Mobasher, B., Moneti, A., Peng, Y., Sanders, D. B., Shuntov, M., Sneppen, A., Valentino, F., Zalesky, L., and Zamorani, G.
Abstract: Context. How galaxies form, assemble, and cease their star formation is a central question within the modern landscape of galaxy evolution studies. These processes are indelibly imprinted on the galaxy stellar mass function (SMF), and its measurement and understanding is key to uncovering a unified theory of galaxy evolution. Aims. We present constraints on the shape and evolution of the galaxy SMF, the quiescent galaxy fraction, and the cosmic stellar mass density across 90% of the history of the Universe from z = 7.5 0.2 as a means to study the physical processes that underpin galaxy evolution. Methods. The COSMOS survey is an ideal laboratory for studying representative galaxy samples. Now equipped with deeper and more homogeneous near-infrared coverage exploited by the COSMOS2020 catalog, we leverage the large 1.27 deg2 effective area to improve sample statistics and understand spatial variations (cosmic variance) particularly for rare, massive galaxies and push to higher redshifts with greater confidence and mass completeness than previous studies. We divide the total stellar mass function into star-forming and quiescent subsamples through NUVrJ color-color selection. The measurements are then fit with single- and double-component Schechter functions to infer the intrinsic galaxy stellar mass function, the evolution of its key parameters, and the cosmic stellar mass density out to z = 7.5. Finally, we compare our measurements to predictions from state-of-the-art cosmological simulations and theoretical dark matter halo mass functions. Results. We find a smooth, monotonic evolution in the galaxy stellar mass function since z = 7.5, in general agreement with previous studies. The number density of star-forming systems have undergone remarkably consistent growth spanning four decades in stellar mass from z = 7.5 2 whereupon high-mass systems become predominantly quiescent ( downsizing ). Meanwhile, the assembly and growth of low-mass quiescent system
Published: 2023

9. The Farmer:A Reproducible Profile-fitting Photometry Package for Deep Galaxy Surveys

Author: Weaver, J. R., Zalesky, L., Kokorev, V., Mc Partland, Conor John Ryan, Chartab, N., Gould, K. M. L., Shuntov, M., Davidzon, I., Faisst, A., Stickley, N., Capak, P. L., Toft, S., Masters, D., Mobasher, B., Sanders, D. B., Kauffmann, O. B., Mccracken, H. J., Ilbert, O., Brammer, G., Moneti, A., Weaver, J. R., Zalesky, L., Kokorev, V., Mc Partland, Conor John Ryan, Chartab, N., Gould, K. M. L., Shuntov, M., Davidzon, I., Faisst, A., Stickley, N., Capak, P. L., Toft, S., Masters, D., Mobasher, B., Sanders, D. B., Kauffmann, O. B., Mccracken, H. J., Ilbert, O., Brammer, G., and Moneti, A.
Published: 2023

10. COSMOS2020: The galaxy stellar mass function: The assembly and star formation cessation of galaxies at 0.2< z ≤ 7.5

Author: Weaver, J. R., Davidzon, I., Toft, S., Ilbert, O., Mccracken, H. J., Gould, K. M. L., Jespersen, C. K., Steinhardt, C., Lagos, C. D. P., Capak, P. L., Casey, C. M., Chartab, N., Faisst, A. L., Hayward, C. C., Kartaltepe, J. S., Kauffmann, O. B., Koekemoer, A. M., Kokorev, V., Laigle, C., Liu, D., Long, A., Magdis, G. E., Mcpartland, C. J. R., Milvang-jensen, B., Mobasher, B., Moneti, A., Peng, Y., Sanders, D. B., Shuntov, M., Sneppen, A., Valentino, F., Zalesky, L., Zamorani, G., Weaver, J. R., Davidzon, I., Toft, S., Ilbert, O., Mccracken, H. J., Gould, K. M. L., Jespersen, C. K., Steinhardt, C., Lagos, C. D. P., Capak, P. L., Casey, C. M., Chartab, N., Faisst, A. L., Hayward, C. C., Kartaltepe, J. S., Kauffmann, O. B., Koekemoer, A. M., Kokorev, V., Laigle, C., Liu, D., Long, A., Magdis, G. E., Mcpartland, C. J. R., Milvang-jensen, B., Mobasher, B., Moneti, A., Peng, Y., Sanders, D. B., Shuntov, M., Sneppen, A., Valentino, F., Zalesky, L., and Zamorani, G.
Published: 2023

11. HSC-CLAUDS survey:The star formation rate functions since z ∼ 2 and comparison with hydrodynamical simulations

Author: Picouet, V., Arnouts, S., Le Floc’h, E., Moutard, T., Kraljic, K., Ilbert, O., Sawicki, M., Desprez, G., Laigle, C., Schiminovich, D., De La Torre, S., Gwyn, S., Mccracken, H. J., Dubois, Y., Davé, R., Toft, S., Weaver, J. R., Shuntov, M., Kauffmann, O. B., Picouet, V., Arnouts, S., Le Floc’h, E., Moutard, T., Kraljic, K., Ilbert, O., Sawicki, M., Desprez, G., Laigle, C., Schiminovich, D., De La Torre, S., Gwyn, S., Mccracken, H. J., Dubois, Y., Davé, R., Toft, S., Weaver, J. R., Shuntov, M., and Kauffmann, O. B.
Published: 2023

12. Euclid preparation:XXVI. the Euclid Morphology Challenge: Towards structural parameters for billions of galaxies

Author: Bretonnière, H., Kuchner, U., Huertas-Company, M., Merlin, E., Castellano, M., Tuccillo, D., Buitrago, F., Conselice, C. J., Boucaud, A., Häuãbler, B., Kümmel, M., Hartley, W. G., Alvarez Ayllon, A., Bertin, E., Ferrari, F., Ferreira, L., Gavazzi, R., Hernández-Lang, D., Lucatelli, G., Robotham, A. S.G., Schefer, M., Wang, L., Cabanac, R., Domínguez Sánchez, H., 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., Iliä, 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., Scott, D., Bretonnière, H., Kuchner, U., Huertas-Company, M., Merlin, E., Castellano, M., Tuccillo, D., Buitrago, F., Conselice, C. J., Boucaud, A., Häuãbler, B., Kümmel, M., Hartley, W. G., Alvarez Ayllon, A., Bertin, E., Ferrari, F., Ferreira, L., Gavazzi, R., Hernández-Lang, D., Lucatelli, G., Robotham, A. S.G., Schefer, M., Wang, L., Cabanac, R., Domínguez Sánchez, H., 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., Iliä, 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.
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 of the Organisational Unit MER of the Euclid Science Ground Segment, we have conducted the Euclid Morphology Challenge, which we present in two papers. While the companion paper focusses 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 (350 000 above 5s) resembling reduced observations with the Euclid VIS and NIR instruments. The simulations include analytic Sérsic 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 Sérsic simulations) down to an apparent magnitude of about IE = 23 in one component and IE = 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 official Euclid 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.
Published: 2023

13. Euclid preparation: XXV. the Euclid Morphology Challenge: Towards model-fitting photometry for billions of galaxies

Author: 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., Häuãler, B., Hartley, W. G., Alvarez Ayllon, A., 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., Iliä, 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., Scott, D., 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., Häuãler, B., Hartley, W. G., Alvarez Ayllon, A., 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., Iliä, 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.
Abstract: The European Space Agency's 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 dataset, and we discuss the photometry results. A companion paper is focussed on the structural and morphological estimates. We created mock Euclid images simulating five fields of view of 0.48 deg2 each in the IE band of the VIS instrument, containing a total of about one and a half million galaxies (of which 350 000 have a nominal signal-to-noise ratio above 5), each with three realisations of galaxy profiles (single and double Sérsic, and 'realistic' profiles obtained with a neural network); for one of the fields in the double Sérsic realisation, we also simulated images for the three near-infrared YE, JE, and HE bands of the NISP-P instrument, and five Rubin/LSST optical complementary bands (u, g, r, i, and z), which together form a typical dataset for an Euclid observation. The images were simulated at the expected Euclid Wide Survey depths. To analyse the results, we created diagnostic plots and defined metrics to take into account the completeness of the provided catalogues, as well as the median biases, dispersions, and outlier fractions of their measured flux distributions. Five model-fitting software packages (DeepLeGATo, Galapagos-2, Morfometryka, ProFit, and SourceXtractor++) were compared, a
Published: 2023

14. Combining the CLAUDS and HSC-SSP surveys U plus grizy(+YJHK(s)) photometry and photometric redshifts for 18M galaxies in the 20 deg(2) 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., Weaver, J. R., 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.
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 similar to 20 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 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 similar to 26, and to magnitude similar to 24.5 in the YJHK(s) bands. We achieve good performance for the photometric redshifts, reaching precisions of sigma(NMAD) less than or similar to 0.04 down to m(i) similar to 25, even using only the CLAUDS and HSC bands. At the same magnitude limit, we measured an outlier fraction of eta less than or similar to 10% when using the Ugrizy bands, and down to eta less than or similar to 6% when considering near-infrared data. The hscPipe plus Phosphoros pipeline performs slightly worse in terms of photometric-redshifts precision and outlier fraction than its SExtractor plus Le Phare counterpart, which
Published: 2023

15. The evolution of the galaxy UV luminosity function at redshifts z similar or equal to 8-15 from deep JWST and ground-based near-infrared imaging

Author: Donnan, C. T., McLeod, D. J., Dunlop, J. S., McLure, R. J., Carnall, A. C., Begley, R., Cullen, F., Hamadouche, M. L., Bowler, R. A. A., Magee, D., McCracken, H. J., Milvang-Jensen, B., Moneti, A., Targett, T., Donnan, C. T., McLeod, D. J., Dunlop, J. S., McLure, R. J., Carnall, A. C., Begley, R., Cullen, F., Hamadouche, M. L., Bowler, R. A. A., Magee, D., McCracken, H. J., Milvang-Jensen, B., Moneti, A., and Targett, T.
Abstract: We reduce and analyse the available JWST ERO and ERS NIRCam imaging (SMACS0723, GLASS, CEERS) in combination with the latest deep ground-based near-infrared imaging in the COSMOS field (provided by UltraVISTA DR5) to produce a new measurement of the evolving galaxy UV luminosity function (LF) over the redshift range z = 8 - 15. This yields a new estimate of the evolution of UV luminosity density (rho(UV)), and hence cosmic star formation rate density (rho(SFR)) out to within = 12, one of which appears to set a new redshift record as an apparently robust galaxy candidate at z similar or equal to 16.4, the properties of which we therefore consider in detail. The advances presented here emphasize the importance of achieving high dynamic range in studies of early galaxy evolution, and re-affirm the enormous potential of forthcoming larger JWST programmes to transform our understanding of the young Universe.
Published: 2023

16. Combining the CLAUDS and HSC-SSP surveys U plus grizy(+YJHK(s)) photometry and photometric redshifts for 18M galaxies in the 20 deg(2) 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., Weaver, J. R., 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.
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 similar to 20 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 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 similar to 26, and to magnitude similar to 24.5 in the YJHK(s) bands. We achieve good performance for the photometric redshifts, reaching precisions of sigma(NMAD) less than or similar to 0.04 down to m(i) similar to 25, even using only the CLAUDS and HSC bands. At the same magnitude limit, we measured an outlier fraction of eta less than or similar to 10% when using the Ugrizy bands, and down to eta less than or similar to 6% when considering near-infrared data. The hscPipe plus Phosphoros pipeline performs slightly worse in terms of photometric-redshifts precision and outlier fraction than its SExtractor plus Le Phare counterpart, which
Published: 2023

17. The evolution of the galaxy UV luminosity function at redshifts z similar or equal to 8-15 from deep JWST and ground-based near-infrared imaging

Author: Donnan, C. T., McLeod, D. J., Dunlop, J. S., McLure, R. J., Carnall, A. C., Begley, R., Cullen, F., Hamadouche, M. L., Bowler, R. A. A., Magee, D., McCracken, H. J., Milvang-Jensen, B., Moneti, A., Targett, T., Donnan, C. T., McLeod, D. J., Dunlop, J. S., McLure, R. J., Carnall, A. C., Begley, R., Cullen, F., Hamadouche, M. L., Bowler, R. A. A., Magee, D., McCracken, H. J., Milvang-Jensen, B., Moneti, A., and Targett, T.
Abstract: We reduce and analyse the available JWST ERO and ERS NIRCam imaging (SMACS0723, GLASS, CEERS) in combination with the latest deep ground-based near-infrared imaging in the COSMOS field (provided by UltraVISTA DR5) to produce a new measurement of the evolving galaxy UV luminosity function (LF) over the redshift range z = 8 - 15. This yields a new estimate of the evolution of UV luminosity density (rho(UV)), and hence cosmic star formation rate density (rho(SFR)) out to within = 12, one of which appears to set a new redshift record as an apparently robust galaxy candidate at z similar or equal to 16.4, the properties of which we therefore consider in detail. The advances presented here emphasize the importance of achieving high dynamic range in studies of early galaxy evolution, and re-affirm the enormous potential of forthcoming larger JWST programmes to transform our understanding of the young Universe.
Published: 2023

18. Euclid preparation:XXVI. The Euclid Morphology Challenge: Towards structural parameters for billions of galaxies

Author: 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., Alvarez Ayllon, A., Bertin, E., Ferrari, F., Ferreira, L., Gavazzi, R., Hernández-lang, D., Lucatelli, G., Robotham, A. S. G., Schefer, M., Wang, L., Cabanac, R., Domínguez Sánchez, H., 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., Scott, D., 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., Alvarez Ayllon, A., Bertin, E., Ferrari, F., Ferreira, L., Gavazzi, R., Hernández-lang, D., Lucatelli, G., Robotham, A. S. G., Schefer, M., Wang, L., Cabanac, R., Domínguez Sánchez, H., 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.
Published: 2023

19. Euclid preparation:XXV. The Euclid Morphology Challenge: Towards model-fitting photometry for billions of galaxies

Author: 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., Alvarez Ayllon, A., 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., Ilić, 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., Scott, D., 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., Alvarez Ayllon, A., 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., Ilić, 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.
Published: 2023

20. The Farmer:A Reproducible Profile-fitting Photometry Package for Deep Galaxy Surveys

Author: Weaver, J. R., Zalesky, L., Kokorev, V., Mc Partland, Conor John Ryan, Chartab, N., Gould, K. M. L., Shuntov, M., Davidzon, I., Faisst, A., Stickley, N., Capak, P. L., Toft, S., Masters, D., Mobasher, B., Sanders, D. B., Kauffmann, O. B., Mccracken, H. J., Ilbert, O., Brammer, G., Moneti, A., Weaver, J. R., Zalesky, L., Kokorev, V., Mc Partland, Conor John Ryan, Chartab, N., Gould, K. M. L., Shuntov, M., Davidzon, I., Faisst, A., Stickley, N., Capak, P. L., Toft, S., Masters, D., Mobasher, B., Sanders, D. B., Kauffmann, O. B., Mccracken, H. J., Ilbert, O., Brammer, G., and Moneti, A.
Published: 2023

21. COSMOS2020: The galaxy stellar mass function: The assembly and star formation cessation of galaxies at 0.2< z ≤ 7.5

Author: Weaver, J. R., Davidzon, I., Toft, S., Ilbert, O., Mccracken, H. J., Gould, K. M. L., Jespersen, C. K., Steinhardt, C., Lagos, C. D. P., Capak, P. L., Casey, C. M., Chartab, N., Faisst, A. L., Hayward, C. C., Kartaltepe, J. S., Kauffmann, O. B., Koekemoer, A. M., Kokorev, V., Laigle, C., Liu, D., Long, A., Magdis, G. E., Mcpartland, C. J. R., Milvang-jensen, B., Mobasher, B., Moneti, A., Peng, Y., Sanders, D. B., Shuntov, M., Sneppen, A., Valentino, F., Zalesky, L., Zamorani, G., Weaver, J. R., Davidzon, I., Toft, S., Ilbert, O., Mccracken, H. J., Gould, K. M. L., Jespersen, C. K., Steinhardt, C., Lagos, C. D. P., Capak, P. L., Casey, C. M., Chartab, N., Faisst, A. L., Hayward, C. C., Kartaltepe, J. S., Kauffmann, O. B., Koekemoer, A. M., Kokorev, V., Laigle, C., Liu, D., Long, A., Magdis, G. E., Mcpartland, C. J. R., Milvang-jensen, B., Mobasher, B., Moneti, A., Peng, Y., Sanders, D. B., Shuntov, M., Sneppen, A., Valentino, F., Zalesky, L., and Zamorani, G.
Published: 2023

22. HSC-CLAUDS survey:The star formation rate functions since z ∼ 2 and comparison with hydrodynamical simulations

Author: Picouet, V., Arnouts, S., Le Floc’h, E., Moutard, T., Kraljic, K., Ilbert, O., Sawicki, M., Desprez, G., Laigle, C., Schiminovich, D., De La Torre, S., Gwyn, S., Mccracken, H. J., Dubois, Y., Davé, R., Toft, S., Weaver, J. R., Shuntov, M., Kauffmann, O. B., Picouet, V., Arnouts, S., Le Floc’h, E., Moutard, T., Kraljic, K., Ilbert, O., Sawicki, M., Desprez, G., Laigle, C., Schiminovich, D., De La Torre, S., Gwyn, S., Mccracken, H. J., Dubois, Y., Davé, R., Toft, S., Weaver, J. R., Shuntov, M., and Kauffmann, O. B.
Published: 2023

23. Euclid preparation:XXV. The Euclid Morphology Challenge: Towards model-fitting photometry for billions of galaxies

Author: 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., Alvarez Ayllon, A., 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., Ilić, 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., Scott, D., 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., Alvarez Ayllon, A., 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., Ilić, 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.
Published: 2023

24. Euclid preparation:XXVI. The Euclid Morphology Challenge: Towards structural parameters for billions of galaxies

Author: 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., Alvarez Ayllon, A., Bertin, E., Ferrari, F., Ferreira, L., Gavazzi, R., Hernández-lang, D., Lucatelli, G., Robotham, A. S. G., Schefer, M., Wang, L., Cabanac, R., Domínguez Sánchez, H., 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., Scott, D., 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., Alvarez Ayllon, A., Bertin, E., Ferrari, F., Ferreira, L., Gavazzi, R., Hernández-lang, D., Lucatelli, G., Robotham, A. S. G., Schefer, M., Wang, L., Cabanac, R., Domínguez Sánchez, H., 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.
Published: 2023

25. Euclid:Searching for pair-instability supernovae with the Deep Survey

Author: Moriya, T. J., Inserra, C., Tanaka, M., Cappellaro, E., Della Valle, M., Hook, I., Kotak, R., Longo, G., Mannucci, F., Mattila, S., Tao, C., Altieri, B., Amara, A., Auricchio, N., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A.J., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V.H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., McCracken, H. J., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Poncet, M., Popa, L., Raison, F., Rhodes, J., Riccio, G., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Scottez, V., Morris, P. W., Moriya, T. J., Inserra, C., Tanaka, M., Cappellaro, E., Della Valle, M., Hook, I., Kotak, R., Longo, G., Mannucci, F., Mattila, S., Tao, C., Altieri, B., Amara, A., Auricchio, N., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A.J., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V.H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., McCracken, H. J., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Poncet, M., Popa, L., Raison, F., Rhodes, J., Riccio, G., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Scottez, V., and Morris, P. W.
Abstract: Pair-instability supernovae are theorized supernovae that have not yet been observationally confirmed. They are predicted to exist in low-metallicity environments. Because overall metallicity becomes lower at higher redshifts, deep near-infrared transient surveys probing high-redshift supernovae are suitable to discover pair-instability supernovae. The Euclid satellite, which is planned launch in 2023, has a near-infrared wide-field instrument that is suitable for a high-redshift supernova survey. The Euclid Deep Survey is planned to make regular observations of three Euclid Deep Fields (40 deg2 in total) spanning Euclid's six-year primary mission period. While the observations of the Euclid Deep Fields are not frequent, we show that the predicted long duration of pair-instability supernovae would allow us to search for high-redshift pair-instability supernovae with the Euclid Deep Survey. Based on the current observational plan of the Euclid mission, we conduct survey simulations in order to estimate the expected numbers of pair-instability supernova discoveries. We find that up to several hundred pair-instability supernovae at z. 3.5 can be discovered within the Euclid Deep Survey. We also show that pair-instability supernova candidates can be efficiently identified by their duration and color, which can be determined with the current Euclid Deep Survey plan. We conclude that the Euclid mission can lead to the first confirmation of pair-instability supernovae if their event rates are as high as those predicted by recent theoretical studies. We also update the expected numbers of superluminous supernova discoveries in the Euclid Deep Survey based on the latest observational plan.
Published: 2022

26. COSMOS2020:UV-selected galaxies at z >= 7.5

Author: Kauffmann, O. B., Ilbert, O., Weaver, J. R., McCracken, H. J., Milvang-Jensen, B., Brammer, G., Davidzon, I., Le Fevre, O., Liu, D., Mobasher, B., Moneti, A., Shuntov, M., Toft, S., Casey, C. M., Dunlop, J. S., Kartaltepe, J. S., Koekemoer, A. M., Sanders, D. B., Tresse, L., Kauffmann, O. B., Ilbert, O., Weaver, J. R., McCracken, H. J., Milvang-Jensen, B., Brammer, G., Davidzon, I., Le Fevre, O., Liu, D., Mobasher, B., Moneti, A., Shuntov, M., Toft, S., Casey, C. M., Dunlop, J. S., Kartaltepe, J. S., Koekemoer, A. M., Sanders, D. B., and Tresse, L.
Abstract: This paper presents a new search for z >= 7.5 galaxies using the COSMOS2020 photometric catalogues. Finding galaxies at the reionisation epoch through deep imaging surveys remains observationally challenging. The larger area covered by ground-based surveys such as COSMOS enables the discovery of the brightest galaxies at these high redshifts. Covering 1.4 deg(2), our COSMOS catalogues were constructed from the latest UltraVISTA data release (DR4) combined with the final Spitzer/IRAC COSMOS images and the Hyper-Suprime-Cam Subaru Strategic Program DR2 release. We identified 17 new 7.5 < z < 10 candidate sources, and confirm 15 previously published candidates. Using deblended photometry extracted by fitting surface brightness models on multi-band images, we selected four candidates which would be rejected using fixed aperture photometry. We tested the robustness of all our candidates by comparing six different photometric redshift estimates. Finally, we computed the galaxy UV luminosity function in three redshift bins centred at z = 8, 9, 10. We find no clear evolution of the number density of the brightest galaxies M-UV < 21 .5, in agreement with previous works. Rapid changes in the quenching efficiency or attenuation by dust could explain such a lack of evolution between z similar to 8 and z similar to 9. A spectroscopic confirmation of the redshifts, already planned with JWST and the Keck telescopes, will be essential to confirm our results.
Published: 2022

27. COSMOS2020:UV-selected galaxies at z >= 7.5

Author: Kauffmann, O. B., Ilbert, O., Weaver, J. R., McCracken, H. J., Milvang-Jensen, B., Brammer, G., Davidzon, I., Le Fevre, O., Liu, D., Mobasher, B., Moneti, A., Shuntov, M., Toft, S., Casey, C. M., Dunlop, J. S., Kartaltepe, J. S., Koekemoer, A. M., Sanders, D. B., Tresse, L., Kauffmann, O. B., Ilbert, O., Weaver, J. R., McCracken, H. J., Milvang-Jensen, B., Brammer, G., Davidzon, I., Le Fevre, O., Liu, D., Mobasher, B., Moneti, A., Shuntov, M., Toft, S., Casey, C. M., Dunlop, J. S., Kartaltepe, J. S., Koekemoer, A. M., Sanders, D. B., and Tresse, L.
Abstract: This paper presents a new search for z >= 7.5 galaxies using the COSMOS2020 photometric catalogues. Finding galaxies at the reionisation epoch through deep imaging surveys remains observationally challenging. The larger area covered by ground-based surveys such as COSMOS enables the discovery of the brightest galaxies at these high redshifts. Covering 1.4 deg(2), our COSMOS catalogues were constructed from the latest UltraVISTA data release (DR4) combined with the final Spitzer/IRAC COSMOS images and the Hyper-Suprime-Cam Subaru Strategic Program DR2 release. We identified 17 new 7.5 < z < 10 candidate sources, and confirm 15 previously published candidates. Using deblended photometry extracted by fitting surface brightness models on multi-band images, we selected four candidates which would be rejected using fixed aperture photometry. We tested the robustness of all our candidates by comparing six different photometric redshift estimates. Finally, we computed the galaxy UV luminosity function in three redshift bins centred at z = 8, 9, 10. We find no clear evolution of the number density of the brightest galaxies M-UV < 21 .5, in agreement with previous works. Rapid changes in the quenching efficiency or attenuation by dust could explain such a lack of evolution between z similar to 8 and z similar to 9. A spectroscopic confirmation of the redshifts, already planned with JWST and the Keck telescopes, will be essential to confirm our results.
Published: 2022

28. COSMOS2020:Manifold learning to estimate physical parameters in large galaxy surveys

Author: Davidzon, I., Jegatheesan, K., Ilbert, O., de la Torre, S., Leslie, S. K., Laigle, C., Hemmati, S., Masters, D. C., Blanquez-Sese, D., Kauffmann, O. B., Magdis, G. E., McCracken, H. J., Mobasher, B., Moneti, A., Sanders, D. B., Shuntov, M., Toft, S., Weaver, J. R., Malek, K., Davidzon, I., Jegatheesan, K., Ilbert, O., de la Torre, S., Leslie, S. K., Laigle, C., Hemmati, S., Masters, D. C., Blanquez-Sese, D., Kauffmann, O. B., Magdis, G. E., McCracken, H. J., Mobasher, B., Moneti, A., Sanders, D. B., Shuntov, M., Toft, S., Weaver, J. R., and Malek, K.
Abstract: We present a novel method for estimating galaxy physical properties from spectral energy distributions (SEDs) as an alternative to template fitting techniques and based on self-organizing maps (SOMs) to learn the high-dimensional manifold of a photometric galaxy catalog. The method has previously been tested with hydrodynamical simulations in Davidzon et al. (2019, MNRAS, 489, 4817), however, here it is applied to real data for the first time. It is crucial for its implementation to build the SOM with a high-quality panchromatic data set, thus we selected "COSMOS2020" galaxy catalog for this purpose. After the training and calibration steps with COSMOS2020, other galaxies can be processed through SOMs to obtain an estimate of their stellar mass and star formation rate (SFR). Both quantities resulted in a good agreement with independent measurements derived from more extended photometric baseline and, in addition, their combination (i.e., the SFR vs. stellar mass diagram) shows a main sequence of star-forming galaxies that is consistent with the findings of previous studies. We discuss the advantages of this method compared to traditional SED fitting, highlighting the impact of replacing the usual synthetic templates with a collection of empirical SEDs built by the SOM in a "data-driven" way. Such an approach also allows, even for extremely large data sets, for an efficient visual inspection to identify photometric errors or peculiar galaxy types. While also considering the computational speed of this new estimator, we argue that it will play a valuable role in the analysis of oncoming large-area surveys such as Euclid of the Legacy Survey of Space and Time at the Vera C. Rubin Telescope.
Published: 2022

29. COSMOS2020:Cosmic evolution of the stellar-to-halo mass relation for central and satellite galaxies up to z similar to 5

Author: Shuntov, M., McCracken, H. J., Gavazzi, R., Laigle, C., Weaver, J. R., Davidzon, I., Ilbert, O., Kauffmann, O. B., Faisst, A., Dubois, Y., Koekemoer, A. M., Moneti, A., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., Toft, S., Shuntov, M., McCracken, H. J., Gavazzi, R., Laigle, C., Weaver, J. R., Davidzon, I., Ilbert, O., Kauffmann, O. B., Faisst, A., Dubois, Y., Koekemoer, A. M., Moneti, A., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., and Toft, S.
Abstract: We used the COSMOS2020 catalog to measure the stellar-to-halo mass relation (SHMR) divided by central and satellite galaxies from z = 0.2 to z = 5.5. Starting from accurate photometric redshifts, we measured the near-infrared selected two-point angular correlation and stellar mass functions in ten redshift bins. We used a phenomenological model that parametrizes the stellar-to-halo mass relation for central galaxies and the number of galaxies inside each halo to describe our observations. This model qualitatively reproduces our measurements and their dependence on the stellar mass threshold. Surprisingly, the mean halo occupation distribution only shows a mild evolution with redshift suggesting that galaxies occupy halos similarly throughout cosmic time. At each redshift, we measured the ratio of stellar mass to halo mass, M-*/M-h, which shows the characteristic strong dependence of halo mass with a peak at M-h(peak) similar to 2 x 10(12) M-circle dot. For the first time, using a joint modeling of clustering and abundances, we measured the evolution of M-h(peak) from z = 0.2 to z = 5.5. M-h(peak) increases gradually with redshift from log M-h(peak)/M-circle dot similar to 12.1 at z similar to 0.3 to log M-h(peak)/M-circle dot similar to 12.3 at z similar to 2, and up to log M-h(peak)/M-circle dot similar to 12.9 at z similar to 5. Similarly, the stellar mass peak M-*(peak) increases with redshift from log M-*(peak)/M-circle dot similar to 10.5 at z similar to 0.3 to log M-*(peak)/M-circle dot similar to 10.9 at z similar to 3. The SHMR ratio at the peak halo mass remains almost constant with redshift. These results are in accordance with the scenario in which the peak of star-formation efficiency moves toward more massive halos at higher redshifts. We also measured the fraction of satellites as a function of stellar mass and redshift. For all stellar mass thresholds, the satellite fraction decreases at higher redshifts. At a given redshift, there is a higher frac
Published: 2022

30. Euclid preparation:XXI. Intermediate-redshift contaminants in the search for z > 6 galaxies within the Euclid Deep Survey

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

31. Euclid preparation:XX. The Complete Calibration of the Color–Redshift Relation survey: LBT observations and data release⋆

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

32. COSMOS2020: Manifold learning to estimate physical parameters in large galaxy surveys

Author: Davidzon, I., Jegatheesan, K., Ilbert, O., de la Torre, S., Leslie, S. K., Laigle, C., Hemmati, S., Masters, D. C., Blanquez-Sese, D., Kauffmann, O. B., Magdis, G. E., McCracken, H. J., Mobasher, B., Moneti, A., Sanders, D. B., Shuntov, M., Toft, S., Weaver, J. R., Malek, K., Davidzon, I., Jegatheesan, K., Ilbert, O., de la Torre, S., Leslie, S. K., Laigle, C., Hemmati, S., Masters, D. C., Blanquez-Sese, D., Kauffmann, O. B., Magdis, G. E., McCracken, H. J., Mobasher, B., Moneti, A., Sanders, D. B., Shuntov, M., Toft, S., Weaver, J. R., and Malek, K.
Abstract: We present a novel method for estimating galaxy physical properties from spectral energy distributions (SEDs) as an alternative to template fitting techniques and based on self-organizing maps (SOMs) to learn the high-dimensional manifold of a photometric galaxy catalog. The method has previously been tested with hydrodynamical simulations in Davidzon et al. (2019, MNRAS, 489, 4817), however, here it is applied to real data for the first time. It is crucial for its implementation to build the SOM with a high-quality panchromatic data set, thus we selected "COSMOS2020" galaxy catalog for this purpose. After the training and calibration steps with COSMOS2020, other galaxies can be processed through SOMs to obtain an estimate of their stellar mass and star formation rate (SFR). Both quantities resulted in a good agreement with independent measurements derived from more extended photometric baseline and, in addition, their combination (i.e., the SFR vs. stellar mass diagram) shows a main sequence of star-forming galaxies that is consistent with the findings of previous studies. We discuss the advantages of this method compared to traditional SED fitting, highlighting the impact of replacing the usual synthetic templates with a collection of empirical SEDs built by the SOM in a "data-driven" way. Such an approach also allows, even for extremely large data sets, for an efficient visual inspection to identify photometric errors or peculiar galaxy types. While also considering the computational speed of this new estimator, we argue that it will play a valuable role in the analysis of oncoming large-area surveys such as Euclid of the Legacy Survey of Space and Time at the Vera C. Rubin Telescope.
Published: 2022

33. COSMOS2020:Manifold learning to estimate physical parameters in large galaxy surveys

Author: Davidzon, I., Jegatheesan, K., Ilbert, O., de la Torre, S., Leslie, S. K., Laigle, C., Hemmati, S., Masters, D. C., Blanquez-Sese, D., Kauffmann, O. B., Magdis, G. E., McCracken, H. J., Mobasher, B., Moneti, A., Sanders, D. B., Shuntov, M., Toft, S., Weaver, J. R., Malek, K., Davidzon, I., Jegatheesan, K., Ilbert, O., de la Torre, S., Leslie, S. K., Laigle, C., Hemmati, S., Masters, D. C., Blanquez-Sese, D., Kauffmann, O. B., Magdis, G. E., McCracken, H. J., Mobasher, B., Moneti, A., Sanders, D. B., Shuntov, M., Toft, S., Weaver, J. R., and Malek, K.
Abstract: We present a novel method for estimating galaxy physical properties from spectral energy distributions (SEDs) as an alternative to template fitting techniques and based on self-organizing maps (SOMs) to learn the high-dimensional manifold of a photometric galaxy catalog. The method has previously been tested with hydrodynamical simulations in Davidzon et al. (2019, MNRAS, 489, 4817), however, here it is applied to real data for the first time. It is crucial for its implementation to build the SOM with a high-quality panchromatic data set, thus we selected "COSMOS2020" galaxy catalog for this purpose. After the training and calibration steps with COSMOS2020, other galaxies can be processed through SOMs to obtain an estimate of their stellar mass and star formation rate (SFR). Both quantities resulted in a good agreement with independent measurements derived from more extended photometric baseline and, in addition, their combination (i.e., the SFR vs. stellar mass diagram) shows a main sequence of star-forming galaxies that is consistent with the findings of previous studies. We discuss the advantages of this method compared to traditional SED fitting, highlighting the impact of replacing the usual synthetic templates with a collection of empirical SEDs built by the SOM in a "data-driven" way. Such an approach also allows, even for extremely large data sets, for an efficient visual inspection to identify photometric errors or peculiar galaxy types. While also considering the computational speed of this new estimator, we argue that it will play a valuable role in the analysis of oncoming large-area surveys such as Euclid of the Legacy Survey of Space and Time at the Vera C. Rubin Telescope.
Published: 2022

34. COSMOS2020:Cosmic evolution of the stellar-to-halo mass relation for central and satellite galaxies up to z similar to 5

Author: Shuntov, M., McCracken, H. J., Gavazzi, R., Laigle, C., Weaver, J. R., Davidzon, I., Ilbert, O., Kauffmann, O. B., Faisst, A., Dubois, Y., Koekemoer, A. M., Moneti, A., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., Toft, S., Shuntov, M., McCracken, H. J., Gavazzi, R., Laigle, C., Weaver, J. R., Davidzon, I., Ilbert, O., Kauffmann, O. B., Faisst, A., Dubois, Y., Koekemoer, A. M., Moneti, A., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., and Toft, S.
Abstract: We used the COSMOS2020 catalog to measure the stellar-to-halo mass relation (SHMR) divided by central and satellite galaxies from z = 0.2 to z = 5.5. Starting from accurate photometric redshifts, we measured the near-infrared selected two-point angular correlation and stellar mass functions in ten redshift bins. We used a phenomenological model that parametrizes the stellar-to-halo mass relation for central galaxies and the number of galaxies inside each halo to describe our observations. This model qualitatively reproduces our measurements and their dependence on the stellar mass threshold. Surprisingly, the mean halo occupation distribution only shows a mild evolution with redshift suggesting that galaxies occupy halos similarly throughout cosmic time. At each redshift, we measured the ratio of stellar mass to halo mass, M-*/M-h, which shows the characteristic strong dependence of halo mass with a peak at M-h(peak) similar to 2 x 10(12) M-circle dot. For the first time, using a joint modeling of clustering and abundances, we measured the evolution of M-h(peak) from z = 0.2 to z = 5.5. M-h(peak) increases gradually with redshift from log M-h(peak)/M-circle dot similar to 12.1 at z similar to 0.3 to log M-h(peak)/M-circle dot similar to 12.3 at z similar to 2, and up to log M-h(peak)/M-circle dot similar to 12.9 at z similar to 5. Similarly, the stellar mass peak M-*(peak) increases with redshift from log M-*(peak)/M-circle dot similar to 10.5 at z similar to 0.3 to log M-*(peak)/M-circle dot similar to 10.9 at z similar to 3. The SHMR ratio at the peak halo mass remains almost constant with redshift. These results are in accordance with the scenario in which the peak of star-formation efficiency moves toward more massive halos at higher redshifts. We also measured the fraction of satellites as a function of stellar mass and redshift. For all stellar mass thresholds, the satellite fraction decreases at higher redshifts. At a given redshift, there is a higher frac
Published: 2022

35. COSMOS2020:A Panchromatic View of the Universe to z ∼ 10 from Two Complementary Catalogs

Author: Weaver, J. R., Kauffmann, O. B., Ilbert, O., McCracken, H. J., Moneti, A., Toft, S., Brammer, G., Shuntov, M., Davidzon, I., Hsieh, B. C., Laigle, C., Anastasiou, A., Jespersen, C. K., Vinther, J., Capak, P., Casey, C. M., McPartland, C. J.R., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., Zalesky, L., Arnouts, S., Aussel, H., Dunlop, J. S., Faisst, A., Franx, M., Furtak, L. J., Fynbo, J. P.U., Gould, K. M.L., Greve, T. R., Gwyn, S., Kartaltepe, J. S., Kashino, D., Koekemoer, A. M., Kokorev, V., Le Fevre, O., Lilly, S., Masters, D., Magdis, G., Mehta, V., Peng, Y., Riechers, D. A., Salvato, M., Sawicki, M., Scarlata, C., Scoville, N., Shirley, R., Silverman, J. D., Sneppen, A., Smolcić, V., Steinhardt, C., Stern, D., Tanaka, M., Taniguchi, Y., Teplitz, H. I., Vaccari, M., Wang, W. H., Zamorani, G., Weaver, J. R., Kauffmann, O. B., Ilbert, O., McCracken, H. J., Moneti, A., Toft, S., Brammer, G., Shuntov, M., Davidzon, I., Hsieh, B. C., Laigle, C., Anastasiou, A., Jespersen, C. K., Vinther, J., Capak, P., Casey, C. M., McPartland, C. J.R., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., Zalesky, L., Arnouts, S., Aussel, H., Dunlop, J. S., Faisst, A., Franx, M., Furtak, L. J., Fynbo, J. P.U., Gould, K. M.L., Greve, T. R., Gwyn, S., Kartaltepe, J. S., Kashino, D., Koekemoer, A. M., Kokorev, V., Le Fevre, O., Lilly, S., Masters, D., Magdis, G., Mehta, V., Peng, Y., Riechers, D. A., Salvato, M., Sawicki, M., Scarlata, C., Scoville, N., Shirley, R., Silverman, J. D., Sneppen, A., Smolcić, V., Steinhardt, C., Stern, D., Tanaka, M., Taniguchi, Y., Teplitz, H. I., Vaccari, M., Wang, W. H., and Zamorani, G.
Abstract: The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data have been collected in the COSMOS field. This paper describes the collection, processing, and analysis of these new imaging data to produce a new reference photometric redshift catalog. Source detection and multiwavelength photometry are performed for 1.7 million sources across the 2 deg2 of the COSMOS field, ∼966,000 of which are measured with all available broadband data using both traditional aperture photometric methods and a new profile-fitting photometric extraction tool, The Farmer, which we have developed. A detailed comparison of the two resulting photometric catalogs is presented. Photometric redshifts are computed for all sources in each catalog utilizing two independent photometric redshift codes. Finally, a comparison is made between the performance of the photometric methodologies and of the redshift codes to demonstrate an exceptional degree of self-consistency in the resulting photometric redshifts. The i < 21 sources have subpercent photometric redshift accuracy and even the faintest sources at 25 < i < 27 reach a precision of 5%. Finally, these results are discussed in the context of previous, current, and future surveys in the COSMOS field. Compared to COSMOS2015, it reaches the same photometric redshift precision at almost one magnitude deeper. Both photometric catalogs and their photometric redshift solutions and physical parameters will be made available through the usual astronomical archive systems (ESO Phase 3, IPAC-IRSA, and CDS).
Published: 2022

36. COSMOS2020:A Panchromatic View of the Universe to z ∼ 10 from Two Complementary Catalogs

Author: Weaver, J. R., Kauffmann, O. B., Ilbert, O., McCracken, H. J., Moneti, A., Toft, S., Brammer, G., Shuntov, M., Davidzon, I., Hsieh, B. C., Laigle, C., Anastasiou, A., Jespersen, C. K., Vinther, J., Capak, P., Casey, C. M., McPartland, C. J.R., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., Zalesky, L., Arnouts, S., Aussel, H., Dunlop, J. S., Faisst, A., Franx, M., Furtak, L. J., Fynbo, J. P.U., Gould, K. M.L., Greve, T. R., Gwyn, S., Kartaltepe, J. S., Kashino, D., Koekemoer, A. M., Kokorev, V., Le Fevre, O., Lilly, S., Masters, D., Magdis, G., Mehta, V., Peng, Y., Riechers, D. A., Salvato, M., Sawicki, M., Scarlata, C., Scoville, N., Shirley, R., Silverman, J. D., Sneppen, A., Smolcić, V., Steinhardt, C., Stern, D., Tanaka, M., Taniguchi, Y., Teplitz, H. I., Vaccari, M., Wang, W. H., Zamorani, G., Weaver, J. R., Kauffmann, O. B., Ilbert, O., McCracken, H. J., Moneti, A., Toft, S., Brammer, G., Shuntov, M., Davidzon, I., Hsieh, B. C., Laigle, C., Anastasiou, A., Jespersen, C. K., Vinther, J., Capak, P., Casey, C. M., McPartland, C. J.R., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., Zalesky, L., Arnouts, S., Aussel, H., Dunlop, J. S., Faisst, A., Franx, M., Furtak, L. J., Fynbo, J. P.U., Gould, K. M.L., Greve, T. R., Gwyn, S., Kartaltepe, J. S., Kashino, D., Koekemoer, A. M., Kokorev, V., Le Fevre, O., Lilly, S., Masters, D., Magdis, G., Mehta, V., Peng, Y., Riechers, D. A., Salvato, M., Sawicki, M., Scarlata, C., Scoville, N., Shirley, R., Silverman, J. D., Sneppen, A., Smolcić, V., Steinhardt, C., Stern, D., Tanaka, M., Taniguchi, Y., Teplitz, H. I., Vaccari, M., Wang, W. H., and Zamorani, G.
Abstract: The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data have been collected in the COSMOS field. This paper describes the collection, processing, and analysis of these new imaging data to produce a new reference photometric redshift catalog. Source detection and multiwavelength photometry are performed for 1.7 million sources across the 2 deg2 of the COSMOS field, ∼966,000 of which are measured with all available broadband data using both traditional aperture photometric methods and a new profile-fitting photometric extraction tool, The Farmer, which we have developed. A detailed comparison of the two resulting photometric catalogs is presented. Photometric redshifts are computed for all sources in each catalog utilizing two independent photometric redshift codes. Finally, a comparison is made between the performance of the photometric methodologies and of the redshift codes to demonstrate an exceptional degree of self-consistency in the resulting photometric redshifts. The i < 21 sources have subpercent photometric redshift accuracy and even the faintest sources at 25 < i < 27 reach a precision of 5%. Finally, these results are discussed in the context of previous, current, and future surveys in the COSMOS field. Compared to COSMOS2015, it reaches the same photometric redshift precision at almost one magnitude deeper. Both photometric catalogs and their photometric redshift solutions and physical parameters will be made available through the usual astronomical archive systems (ESO Phase 3, IPAC-IRSA, and CDS).
Published: 2022

37. COSMOS2020: A Panchromatic View of the Universe to z ∼ 10 from Two Complementary Catalogs

Author: Weaver, J. R., Kauffmann, O. B., Ilbert, O., McCracken, H. J., Moneti, A., Toft, S., Brammer, G., Shuntov, M., Davidzon, I., Hsieh, B. C., Laigle, C., Anastasiou, A., Jespersen, C. K., Vinther, J., Capak, P., Casey, C. M., McPartland, C. J. R., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., Zalesky, L., Arnouts, S., Aussel, H., Dunlop, J. S., Faisst, A., Franx, M., Furtak, L. J., Fynbo, J. P. U., Gould, K. M. L., Greve, T. R., Gwyn, S., Kartaltepe, J. S., Kashino, D., Koekemoer, A. M., Kokorev, V., Le Fèvre, O., Lilly, S., Masters, D., Magdis, G., Mehta, V., Peng, Y., Riechers, D. A., Salvato, M., Sawicki, M., Scarlata, C., Scoville, N., Shirley, R., Silverman, J. D., Sneppen, A., Smolc̆ić, V., Steinhardt, C., Stern, D., Tanaka, M., Taniguchi, Y., Teplitz, H. I., Vaccari, M., Wang, W.-H., Zamorani, G., Weaver, J. R., Kauffmann, O. B., Ilbert, O., McCracken, H. J., Moneti, A., Toft, S., Brammer, G., Shuntov, M., Davidzon, I., Hsieh, B. C., Laigle, C., Anastasiou, A., Jespersen, C. K., Vinther, J., Capak, P., Casey, C. M., McPartland, C. J. R., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., Zalesky, L., Arnouts, S., Aussel, H., Dunlop, J. S., Faisst, A., Franx, M., Furtak, L. J., Fynbo, J. P. U., Gould, K. M. L., Greve, T. R., Gwyn, S., Kartaltepe, J. S., Kashino, D., Koekemoer, A. M., Kokorev, V., Le Fèvre, O., Lilly, S., Masters, D., Magdis, G., Mehta, V., Peng, Y., Riechers, D. A., Salvato, M., Sawicki, M., Scarlata, C., Scoville, N., Shirley, R., Silverman, J. D., Sneppen, A., Smolc̆ić, V., Steinhardt, C., Stern, D., Tanaka, M., Taniguchi, Y., Teplitz, H. I., Vaccari, M., Wang, W.-H., and Zamorani, G.
Abstract: The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data have been collected in the COSMOS field. This paper describes the collection, processing, and analysis of these new imaging data to produce a new reference photometric redshift catalog. Source detection and multiwavelength photometry are performed for 1.7 million sources across the 2 deg2 of the COSMOS field, ∼966,000 of which are measured with all available broadband data using both traditional aperture photometric methods and a new profile-fitting photometric extraction tool, The Farmer, which we have developed. A detailed comparison of the two resulting photometric catalogs is presented. Photometric redshifts are computed for all sources in each catalog utilizing two independent photometric redshift codes. Finally, a comparison is made between the performance of the photometric methodologies and of the redshift codes to demonstrate an exceptional degree of self-consistency in the resulting photometric redshifts. The i < 21 sources have subpercent photometric redshift accuracy and even the faintest sources at 25 < i < 27 reach a precision of 5%. Finally, these results are discussed in the context of previous, current, and future surveys in the COSMOS field. Compared to COSMOS2015, it reaches the same photometric redshift precision at almost one magnitude deeper. Both photometric catalogs and their photometric redshift solutions and physical parameters will be made available through the usual astronomical archive systems (ESO Phase 3, IPAC-IRSA, and CDS).
Published: 2022

38. Euclid preparation : XVII. Cosmic Dawn Survey: Spitzer Space Telescope observations of the Euclid deep fields and calibration fields

Author: Euclid Collaboration, Moneti, A, McCracken, H J, Shuntov, M, et al, Potter, Douglas; https://orcid.org/0000-0002-0757-5195, Euclid Collaboration, Moneti, A, McCracken, H J, Shuntov, M, et al, and Potter, Douglas; https://orcid.org/0000-0002-0757-5195
Published: 2022

39. The Farmer: A reproducible profile-fitting photometry package for deep galaxy surveys

Author: Weaver, J. R., Zalesky, L., Kokorev, V., McPartland, C. J. R., Chartab, N., Gould, K. M. L., Shuntov, M., Davidzon, I., Faisst, A., Stickley, N., Capak, P. L., Toft, S., Masters, D., Mobasher, B., Sanders, D. B., Kauffmann, O. B., McCracken, H. J., Ilbert, O., Brammer, G., Moneti, A., Weaver, J. R., Zalesky, L., Kokorev, V., McPartland, C. J. R., Chartab, N., Gould, K. M. L., Shuntov, M., Davidzon, I., Faisst, A., Stickley, N., Capak, P. L., Toft, S., Masters, D., Mobasher, B., Sanders, D. B., Kauffmann, O. B., McCracken, H. J., Ilbert, O., Brammer, G., and Moneti, A.
Abstract: While space-borne optical and near-infrared facilities have succeeded in delivering a precise and spatially resolved picture of our Universe, their small survey area is known to under-represent the true diversity of galaxy populations. Ground-based surveys have reached comparable depths but at lower spatial resolution, resulting in source confusion that hampers accurate photometry extractions. What once was limited to the infrared regime has now begun to challenge ground-based ultra-deep surveys, affecting detection and photometry alike. Failing to address these challenges will mean forfeiting a representative view into the distant Universe. We introduce The Farmer: an automated, reproducible profile-fitting photometry package that pairs a library of smooth parametric models from The Tractor (Lang et al. 2016) with a decision tree that determines the best-fit model in concert with neighboring sources. Photometry is measured by fitting the models on other bands leaving brightness free to vary. The resulting photometric measurements are naturally total, and no aperture corrections are required. Supporting diagnostics (e.g. $\chi^2$) enable measurement validation. As fitting models is relatively time intensive, The Farmer is built with high-performance computing routines. We benchmark The Farmer on a set of realistic COSMOS-like images and find accurate photometry, number counts, and galaxy shapes. The Farmer is already being utilized to produce catalogs for several large-area deep extragalactic surveys where it has been shown to tackle some of the most challenging optical and near-infrared data available, with the promise of extending to other ultra-deep surveys expected in the near future. The Farmer is available to download from GitHub and Zenodo., Comment: 30 pages, 17 figures, accepted for publication in ApJS. The Farmer software is publicly accessible on Github at https://github.com/astroweaver/the_farmer
Published: 2023

40. The COSMOS-Web ring: in-depth characterization of an Einstein ring lensing system at z~2

Author: Mercier, W., Shuntov, M., Gavazzi, R., Nightingale, J. W., Arango, R., Ilbert, O., Amvrosiadis, A., Ciesla, L., Casey, C., Jin, S., Faisst, A. L., Andika, I. T., Drakos, N. E., Enia, A., Franco, M., Gillman, S., Gozaliasl, G., Hayward, C. C., Huertas-Company, M., Kartaltepe, J. S., Koekemoer, A. M., Laigle, C., Borgne, D. Le, Magdis, G., Mahler, G., Maraston, C., Martin, C. L., Massey, R., McCracken, H. J., Moutard, T., Paquereau, L., Rhodes, J. D., Robertson, B. E., Sanders, D. B., Trebitsch, M., Tresse, L., Vijayan, A. P., Mercier, W., Shuntov, M., Gavazzi, R., Nightingale, J. W., Arango, R., Ilbert, O., Amvrosiadis, A., Ciesla, L., Casey, C., Jin, S., Faisst, A. L., Andika, I. T., Drakos, N. E., Enia, A., Franco, M., Gillman, S., Gozaliasl, G., Hayward, C. C., Huertas-Company, M., Kartaltepe, J. S., Koekemoer, A. M., Laigle, C., Borgne, D. Le, Magdis, G., Mahler, G., Maraston, C., Martin, C. L., Massey, R., McCracken, H. J., Moutard, T., Paquereau, L., Rhodes, J. D., Robertson, B. E., Sanders, D. B., Trebitsch, M., Tresse, L., and Vijayan, A. P.
Abstract: Aims. We provide an in-depth analysis of the COSMOS-Web ring, an Einstein ring at z=2 that we serendipitously discovered in the COSMOS-Web survey and possibly the most distant lens discovered to date. Methods. We extract the visible and NIR photometry from more than 25 bands and we derive the photometric redshifts and physical properties of both the lens and the source with three different SED fitting codes. Using JWST/NIRCam images, we also produce two lens models to (i) recover the total mass of the lens, (ii) derive the magnification of the system, (iii) reconstruct the morphology of the lensed source, and (iv) measure the slope of the total mass density profile of the lens. Results. The lens is a very massive and quiescent (sSFR < 10^(-13) yr-1) elliptical galaxy at z = 2.02 \pm 0.02 with a total mass Mtot(
Published: 2023

41. HSC-CLAUDS survey: The star formation rate functions since z ~ 2 and comparison with hydrodynamical simulations

Author: Picouet, V., Arnouts, S., Floch, E. Le, Moutard, T., Kraljic, K., Ilbert, O., Sawicki, M., Desprez, G., Laigle, C., Schiminovich, D., de la Torre, S., Gwyn, S., McCracken, H. J., Dubois, Y., Davé, R., Toft, S., Weaver, J. R., Shuntov, M., Kauffmann, O. B., Picouet, V., Arnouts, S., Floch, E. Le, Moutard, T., Kraljic, K., Ilbert, O., Sawicki, M., Desprez, G., Laigle, C., Schiminovich, D., de la Torre, S., Gwyn, S., McCracken, H. J., Dubois, Y., Davé, R., Toft, S., Weaver, J. R., Shuntov, M., and Kauffmann, O. B.
Abstract: Star formation rate functions (SFRFs) give an instantaneous view of the distribution of star formation rates (SFRs) in galaxies at different epochs. They are a complementary and more stringent test for models than the galaxy stellar mass function, which gives an integrated view of the past star formation activity. However, the exploration of SFRFs has been limited thus far due to difficulties in assessing the SFR from observed quantities and probing the SFRF over a wide range of SFRs. We overcome these limitations thanks to an original method that predicts the infrared luminosity from the rest-frame UV/optical color of a galaxy and then its SFR over a wide range of stellar masses and redshifts. We applied this technique to the deep imaging survey HSC-CLAUDS combined with near-infrared and UV photometry. We provide the first SFR functions with reliable measurements in the high- and low-SFR regimes up to $z=2$ and compare our results with previous observations and four state-of-the-art hydrodynamical simulations., Comment: 29 pages, 19 figures
Published: 2023
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42. 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., Weaver, J. R., 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.
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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43. DEIMOS spectroscopy of $z=6$ protocluster candidate in COSMOS -- A massive protocluster embedded in a large scale structure?

Author: Brinch, Malte, Greve, Thomas R., Sanders, David B., McPartland, Conor J. R., Chartab, Nima, Gillman, Steven, Vijayan, Aswin P., Lee, Minju M., Brammer, Gabriel, Casey, Caitlin M., Ilbert, Olivier, Jin, Shuowen, Magdis, Georgios, McCracken, H. J., Sillassen, Nikolaj B., Toft, Sune, Zavala, Jorge A., Brinch, Malte, Greve, Thomas R., Sanders, David B., McPartland, Conor J. R., Chartab, Nima, Gillman, Steven, Vijayan, Aswin P., Lee, Minju M., Brammer, Gabriel, Casey, Caitlin M., Ilbert, Olivier, Jin, Shuowen, Magdis, Georgios, McCracken, H. J., Sillassen, Nikolaj B., Toft, Sune, and Zavala, Jorge A.
Abstract: We present the results of our Keck/DEIMOS spectroscopic follow-up of candidate galaxies of i-band-dropout protocluster candidate galaxies at $z\sim6$ in the COSMOS field. We securely detect Lyman-$\alpha$ emission lines in 14 of the 30 objects targeted, 10 of them being at $z=6$ with a signal-to-noise ratio of $5-20$, the remaining galaxies are either non-detections or interlopers with redshift too different from $z=6$ to be part of the protocluster. The 10 galaxies at $z\approx6$ make the protocluster one of the riches at $z>5$. The emission lines exhibit asymmetric profiles with high skewness values ranging from 2.87 to 31.75, with a median of 7.37. This asymmetry is consistent with them being Ly$\alpha$, resulting in a redshift range of $z=5.85-6.08$. Using the spectroscopic redshifts, we re-calculate the overdensity map for the COSMOS field and find the galaxies to be in a significant overdensity at the $4\sigma$ level, with a peak overdensity of $\delta=11.8$ (compared to the previous value of $\delta=9.2$). The protocluster galaxies have stellar masses derived from Bagpipes SED fits of $10^{8.29}-10^{10.28} \rm \,M_{\rm \odot}$ and star formation rates of $2-39\,\rm M_{\rm \odot}\rm\,yr^{-1}$, placing them on the main sequence at this epoch. Using a stellar-to-halo-mass relationship, we estimate the dark matter halo mass of the most massive halo in the protocluster to be $\sim 10^{12}\rm M_{\rm \odot}$. By comparison with halo mass evolution tracks from simulations, the protocluster is expected to evolve into a Virgo- or Coma-like cluster in the present day., Comment: 26 pages, 14 figues, 5 tables, main text is 16 pages, appendix is 10 pages, published in MNRAS
Published: 2023

44. 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., Weaver, J. R., 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.
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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45. Euclid: Discovering pair-instability supernovae with the Deep Survey

Author: Moriya, T. J., Inserra, C., Tanaka, M., Cappellaro, E., Della Valle, M., Hook, I., Kotak, R., Longo, G., Mannucci, F., Mattila, S., Tao, C., Altieri, B., Amara, A., Auricchio, N., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Poncet, M., Popa, L., Raison, F., Rhodes, J., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Camera, S., McCracken, H. J., Riccio, G., Scottez, V., Moriya, T. J., Inserra, C., Tanaka, M., Cappellaro, E., Della Valle, M., Hook, I., Kotak, R., Longo, G., Mannucci, F., Mattila, S., Tao, C., Altieri, B., Amara, A., Auricchio, N., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Melchior, M., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Poncet, M., Popa, L., Raison, F., Rhodes, J., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Camera, S., McCracken, H. J., Riccio, G., and Scottez, V.
Abstract: Pair-instability supernovae are theorized supernovae that have not yet been observationally confirmed. They are predicted to exist in low-metallicity environments. Because overall metallicity becomes lower at higher redshifts, deep near-infrared transient surveys probing high-redshift supernovae are suitable to discover pair-instability supernovae. The Euclid satellite, which is planned to be launched in 2023, has a near-infrared wide-field instrument that is suitable for a high-redshift supernova survey. Although no dedicated supernova survey is currently planned during the Euclid's 6 year primary mission, the Euclid Deep Survey is planned to make regular observations of three Euclid Deep Fields (40 deg2 in total) spanning six years. While the observations of the Euclid Deep Fields are not frequent, we show that the predicted long duration of pair-instability supernovae would allow us to search for high-redshift pair-instability supernovae with the Euclid Deep Survey. Based on the current observational plan of the Euclid mission, we conduct survey simulations in order to estimate the expected numbers of pair-instability supernova discoveries. We find that up to several hundred pair-instability supernovae at z < ~ 3.5 can be discovered by the Euclid Deep Survey. We also show that pair-instability supernova candidates can be efficiently identified by their duration and color that can be determined with the current Euclid Deep Survey plan. We conclude that the Euclid mission can lead to the first confident discovery of pair-instability supernovae if their event rates are as high as those predicted by recent theoretical studies. We also update the expected numbers of superluminous supernova discoveries in the Euclid Deep Survey based on the latest observational plan., Comment: 12 pages, 13 figures, 2 tables, submitted to Astronomy & Astrophysics
Published: 2022

46. COSMOS2020: The cosmic evolution of the stellar-to-halo mass relation for central and satellite galaxies up to z~5

Author: Shuntov, M., McCracken, H. J., Gavazzi, R., Laigle, C., Weaver, J. R., Davidzon, I., Ilbert, O., Kauffmann, O. B., Faisst, A., Dubois, Y., Koekemoer, A. M., Moneti, A., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., Toft, S., Shuntov, M., McCracken, H. J., Gavazzi, R., Laigle, C., Weaver, J. R., Davidzon, I., Ilbert, O., Kauffmann, O. B., Faisst, A., Dubois, Y., Koekemoer, A. M., Moneti, A., Milvang-Jensen, B., Mobasher, B., Sanders, D. B., and Toft, S.
Abstract: We use the COSMOS2020 catalogue to measure the stellar-to-halo mass relation (SHMR) divided by central and satellite galaxies from $z=0.2$ to $z = 5.5$. Starting from accurate photometric redshifts we measure the near-infrared selected two-point angular correlation and stellar mass functions in ten redshift bins and fit them with an HOD-based model. At each redshift, we measure the ratio of stellar mass to halo mass, $M_*/M_h$, which shows the characteristic strong dependence of halo mass with a peak at $M_h^{\rm peak} \sim 2$. Our results are in accordance with the scenario in which the peak of star-formation efficiency moves towards more massive halos at higher redshifts. We also measure the fraction of satellites as a function of stellar mass and redshift. For all stellar mass thresholds the satellite fraction decreases at higher redshifts. At a given redshift there is a higher fraction of low-mass satellites. The satellite contribution to the total stellar mass budget in halos becomes more important than centrals at halo masses of about $M_h > 10^{13} \, M_{\odot}$ and always stays below by peak, indicating that quenching mechanisms are present in massive halos that keep the star-formation efficiency low. Finally, we compare our results with three hydrodynamical simulations Horizon-AGN, Illustris-TNG-100 and EAGLE. We find that the most significant discrepancy is at the high mass end, where the simulations generally show that satellites have a higher contribution to the total stellar mass budget than the observations. This, together with the finding that the fraction of satellites is higher in the simulations, indicates that the feedback mechanisms acting in group-and cluster-scale halos appear to be less efficient in quenching the mass assembly of satellites, and/or that quenching occurs much later in the simulations.
Published: 2022

47. Euclid preparation. XVIII. The NISP photometric system

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

48. COSMOS2020: The Galaxy Stellar Mass Function: the assembly and star formation cessation of galaxies at $0.2\lt z \leq 7.5$

Author: Weaver, J. R., Davidzon, I., Toft, S., Ilbert, O., McCracken, H. J., Gould, K. M. L., Jespersen, C. K., Steinhardt, C., Lagos, C. D. P., Capak, P. L., Casey, C. M., Chartab, N., Faisst, A. L., Hayward, C. C., Kartaltepe, J. S., Kauffmann, O. B., Koekemoer, A. M., Kokorev, V., Laigle, C., Liu, D., Long, A., Magdis, G. E., McPartland, C. J. R., Milvang-Jensen, B., Mobasher, B., Moneti, A., Peng, Y., Sanders, D. B., Shuntov, M., Sneppen, A., Valentino, F., Zalesky, L., Zamorani, G., Weaver, J. R., Davidzon, I., Toft, S., Ilbert, O., McCracken, H. J., Gould, K. M. L., Jespersen, C. K., Steinhardt, C., Lagos, C. D. P., Capak, P. L., Casey, C. M., Chartab, N., Faisst, A. L., Hayward, C. C., Kartaltepe, J. S., Kauffmann, O. B., Koekemoer, A. M., Kokorev, V., Laigle, C., Liu, D., Long, A., Magdis, G. E., McPartland, C. J. R., Milvang-Jensen, B., Mobasher, B., Moneti, A., Peng, Y., Sanders, D. B., Shuntov, M., Sneppen, A., Valentino, F., Zalesky, L., and Zamorani, G.
Abstract: How galaxies form, assemble, and cease their star-formation is a central question within the modern landscape of galaxy evolution studies. These processes are indelibly imprinted on the galaxy stellar mass function (SMF). We present constraints on the shape and evolution of the SMF, the quiescent galaxy fraction, and the cosmic stellar mass density across 90% of the history of the Universe from $z=7.5\rightarrow0.2$ via the COSMOS survey. Now with deeper and more homogeneous near-infrared coverage exploited by the COSMOS2020 catalog, we leverage the large 1.27 deg$^{2}$ effective area to improve sample statistics and understand cosmic variance particularly for rare, massive galaxies and push to higher redshifts with greater confidence and mass completeness than previous studies. We divide the total stellar mass function into star-forming and quiescent sub-samples through $NUVrJ$ color-color selection. Measurements are then fitted with Schechter functions to infer the intrinsic SMF, the evolution of its key parameters, and the cosmic stellar mass density out to $z=7.5$. We find a smooth, monotonic evolution in the galaxy SMF since $z=7.5$, in agreement with previous studies. The number density of star-forming systems seems to have undergone remarkably consistent growth spanning four decades in stellar mass from $z=7.5\rightarrow2$ whereupon high-mass systems become predominantly quiescent (i.e. downsizing). An excess of massive systems at $z\sim2.5-5.5$ with strikingly red colors, some newly identified, increase the observed number densities to the point where the SMF cannot be reconciled with a Schechter function. Systematics including cosmic variance and/or AGN contamination are unlikely to fully explain this excess, and so we speculate that there may be contributions from dust-obscured objects similar to those found in FIR surveys. (abridged), Comment: 39 pages, 24 figures, accepted for publication in A&A. Data files containing key measurements are available for download: https://doi.org/10.5281/zenodo.7808832
Published: 2022
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49. COSMOS2020: Identification of High-z Protocluster Candidates in COSMOS

Author: Brinch, Malte, Greve, Thomas R., Weaver, John R., Brammer, Gabriel, Ilbert, Olivier, Shuntov, Marko, Jin, Shuowen, Liu, Daizhong, Giménez-Arteaga, Clara, Casey, Caitlin M., Davidson, Iary, Fujimoto, Seiji, Koekemoer, Anton M., Kokorev, Vasily, Magdis, Georgios, McCracken, H. J., McPartland, Conor J. R., Mobasher, Bahram, Sanders, David B., Toft, Sune, Valentino, Francesco, Zamorani, Giovanni, Zavala, Jorge, Brinch, Malte, Greve, Thomas R., Weaver, John R., Brammer, Gabriel, Ilbert, Olivier, Shuntov, Marko, Jin, Shuowen, Liu, Daizhong, Giménez-Arteaga, Clara, Casey, Caitlin M., Davidson, Iary, Fujimoto, Seiji, Koekemoer, Anton M., Kokorev, Vasily, Magdis, Georgios, McCracken, H. J., McPartland, Conor J. R., Mobasher, Bahram, Sanders, David B., Toft, Sune, Valentino, Francesco, Zamorani, Giovanni, and Zavala, Jorge
Abstract: We conduct a systematic search for protocluster candidates at $z \geq 6$ in the COSMOS field using the recently released COSMOS2020 source catalog. We select galaxies using a number of selection criteria to obtain a sample of galaxies that have a high probability of being inside a given redshift bin. We then apply overdensity analysis to the bins using two density estimators, a Weighted Adaptive Kernel Estimator and a Weighted Voronoi Tessellation Estimator. We have found 15 significant ($>4\sigma$) candidate galaxy overdensities across the redshift range $6\le z\le7.7$. The majority of the galaxies appear to be on the galaxy main sequence at their respective epochs. We use multiple stellar-mass-to-halo-mass conversion methods to obtain a range of dark matter halo mass estimates for the overdensities in the range of $\sim10^{11-13}\,M_{\rm \odot}$, at the respective redshifts of the overdensities. The number and the masses of the halos associated with our protocluster candidates are consistent with what is expected from the area of a COSMOS-like survey in a standard $\Lambda$CDM cosmology. Through comparison with simulation, we expect that all the overdensities at $z\simeq6$ will evolve into a Virgo-/Coma-like clusters at present (i.e., with masses $\sim 10^{14}-10^{15}\,M_{\rm \odot}$). Compared to other overdensities identified at $z \geq 6$ via narrow-band selection techniques, the overdensities presented appear to have $\sim10\times$ higher stellar masses and star-formation rates. We compare the evolution in the total star-formation rate and stellar mass content of the protocluster candidates across the redshift range $6\le z\le7.7$ and find agreement with the total average star-formation rate from simulations., Comment: 52 pages, 32 figues, 18 tables, main text is 30 pages, appendix is 22 pages, to be published in ApJ
Published: 2022
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50. 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., Scott, D., 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.
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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