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

S. E. Van Mierlo, K. I. Caputi, M. Ashby, H. Atek, M. Bolzonella, R. A.A. Bowler, G. Brammer, C. J. Conselice, J. Cuby, P. Dayal, A. Díaz-Sánchez, S. L. Finkelstein, H. Hoekstra, A. Humphrey, O. Ilbert, H. J. McCracken, B. Milvang-Jensen, P. A. Oesch, R. Pello, G. RodighieroM. Schirmer, S. Toft, J. R. Weaver, S. M. Wilkins, C. J. Willott, G. Zamorani, A. Amara, N. Auricchio, M. Baldi, R. Bender, C. Bodendorf, D. Bonino, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, V. Capobianco, C. Carbone, J. Carretero, M. Castellano, S. Cavuoti, A. Cimatti, R. Cledassou, G. Congedo, L. Conversi, Y. Copin, L. Corcione, F. Courbin, A. Da Silva, H. Degaudenzi, M. Douspis, F. Dubath, X. Dupac, S. Dusini, S. Farrens, S. Ferriol, M. Frailis, E. Franceschi, P. Franzetti, M. Fumana, S. Galeotta, B. Garilli, W. Gillard, B. Gillis, C. Giocoli, A. Grazian, F. Grupp, S. V.H. Haugan, W. Holmes, F. Hormuth, A. Hornstrup, K. Jahnke, M. Kümmel, A. Kiessling, M. Kilbinger, T. Kitching, R. Kohley, M. Kunz, H. Kurki-Suonio, R. Laureijs, S. Ligori, P. B. Lilje, I. Lloro, E. Maiorano, O. Mansutti, O. Marggraf, K. Markovic, F. Marulli, R. Massey, S. Maurogordato, E. Medinaceli, M. Meneghetti, E. Merlin, G. Meylan, M. Moresco, L. Moscardini, E. Munari, S. M. Niemi, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, V. Pettorino, S. Pires, M. Poncet, L. Popa, L. Pozzetti, F. Raison, A. Renzi, J. Rhodes, G. Riccio, E. Romelli, E. Rossetti, R. Saglia, D. Sapone, B. Sartoris, P. Schneider, A. Secroun, C. Sirignano, G. Sirri, L. Stanco, J. L. Starck, C. Surace, P. Tallada-Crespí, A. N. Taylor, I. Tereno, R. Toledo-Moreo, F. Torradeflot, I. Tutusaus, E. A. Valentijn, L. Valenziano, T. Vassallo, Y. Wang, A. Zacchei, J. Zoubian, S. Andreon, S. Bardelli, A. Boucaud, J. Graciá-Carpio, D. Maino, N. Mauri, S. Mei, F. Sureau, E. Zucca, H. Aussel, C. Baccigalupi, A. Balaguera-Antolínez, A. Biviano, A. Blanchard, S. Borgani, E. Bozzo, C. Burigana, R. Cabanac, F. Calura, A. Cappi, C. S. Carvalho, S. Casas, G. Castignani, C. Colodro-Conde, A. R. Cooray, J. Coupon, H. M. Courtois, M. Crocce, O. Cucciati, S. Davini, H. Dole, J. A. Escartin, S. Escoffier, M. Fabricius, M. Farina, K. Ganga, J. García-Bellido, K. George, F. Giacomini, G. Gozaliasl, S. Gwyn, I. Hook, M. Huertas-Company, V. Kansal, A. Kashlinsky, E. Keihanen, C. C. Kirkpatrick, V. Lindholm, R. Maoli, M. Martinelli, N. Martinet, M. Maturi, R. B. Metcalf, P. Monaco, G. Morgante, A. A. Nucita, L. Patrizii, A. Peel, J. Pollack, V. Popa, C. Porciani, D. Potter, P. Reimberg, A. G. Sánchez, V. Scottez, E. Sefusatti, J. Stadel, R. Teyssier, J. Valiviita, M. Viel

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Context. The Euclid mission is expected to discover thousands of z > 6 galaxies in three deep fields, which together will cover a ∼50 deg2area. 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 deg2area 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 5O detection threshold requirement in at least one of the Euclid near-infrared bands reduces the contamination fraction to 25%.

Original languageEnglish (US)
Article numberA200
JournalAstronomy and Astrophysics
Volume666
DOIs
StatePublished - Oct 1 2022

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

Keywords

  • Galaxies: evolution
  • Galaxies: high-redshift
  • Galaxies: photometry

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