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 contaminants as many have unconstrained (IE − YE) colours. In the best scenario, these cuts reduce the contamination fraction to 1% whilst preserving 81% of the fiducial z > 6 sample. For the faint mock sample, colour cuts are infeasible; we find instead that a 5σ detection threshold requirement in at least one of the Euclid near-infrared bands reduces the contamination fraction to 25%.
Euclid preparation: XXI. Intermediate-redshift contaminants in the search for z > 6 galaxies within the Euclid Deep Survey (vol 666, A200, 2022) / van Mierlo, Se; Caputi, Ki; Ashby, M; Atek, H; Bolzonella, M; Bowler, Raa; Brammer, G; Conselice, Cj; Cuby, J; Dayal, P; Diaz-Sanchez, A; Finkelstein, Sl; Hoekstra, H; Humphrey, A; Ilbert, O; Mccracken, Hj; Milvang-Jensen, B; Oesch, Pa; Pello, R; Rodighiero, G; Schirmer, M; Toft, S; Weaver, Jr; Wilkins, Sm; Willott, Cj; 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, Svh; Holmes, W; Hormuth, F; Hornstrup, A; Jahnke, K; Kummel, M; Kiessling, A; Kilbinger, M; Kitching, T; Kohley, R; Kunz, M; Kurki-Suonio, H; Laureijs, R; Ligori, S; Lilje, Pb; 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, Sm; 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, Jl; Surace, C; Tallada-Crespi, P; Taylor, An; Tereno, I; Toledo-Moreo, R; Torradeflot, F; Tutusaus, I; Valentijn, Ea; Valenziano, L; Vassallo, T; Wang, Y; Zacchei, A; Zoubian, J; Andreon, S; Bardelli, S; Boucaud, A; Gracia-Carpio, J; Maino, D; Mauri, N; Mei, S; Sureau, F; Zucca, E; Aussel, H; Baccigalupi, C; Balaguera-Antolinez, A; Biviano, A; Blanchard, A; Borgani, S; Bozzo, E; Burigana, C; Cabanac, R; Calura, F; Cappi, A; Carvalho, Cs; Casas, S; Castignani, G; Colodro-Conde, C; Cooray, Ar; Coupon, J; Courtois, Hm; Crocce, M; Cucciati, O; Davini, S; Dole, H; Escartin, Ja; Escoffier, S; Fabricius, M; Farina, M; Ganga, K; Garcia-Bellido, J; George, K; Giacomini, F; Gozaliasl, G; Gwyn, S; Hook, I; Huertas-Company, M; Kansal, V; Kashlinsky, A; Keihanen, E; Kirkpatrick, Cc; Lindholm, V; Maoli, R; Martinelli, M; Martinet, N; Maturi, M; Metcalf, Rb; Monaco, P; Morgante, G; Nucita, Aa; Patrizii, L; Peel, A; Pollack, J; Popa, V; Porciani, C; Potter, D; Reimberg, P; Sanchez, Ag; Scottez, V; Sefusatti, E; Stadel, J; Teyssier, R; Valiviita, J; Viel, M. - In: ASTRONOMY & ASTROPHYSICS. - ISSN 0004-6361. - 668:(2022). [10.1051/0004-6361/202243950e]
Euclid preparation: XXI. Intermediate-redshift contaminants in the search for z > 6 galaxies within the Euclid Deep Survey (vol 666, A200, 2022)
Maoli, R;
2022
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 contaminants as many have unconstrained (IE − YE) colours. In the best scenario, these cuts reduce the contamination fraction to 1% whilst preserving 81% of the fiducial z > 6 sample. For the faint mock sample, colour cuts are infeasible; we find instead that a 5σ detection threshold requirement in at least one of the Euclid near-infrared bands reduces the contamination fraction to 25%.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
