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

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Euclid preparation: XXI. Intermediate-redshift contaminants in the search for z>6 galaxies within the Euclid Deep Survey. / Euclid Collaboration.
In: Astronomy and Astrophysics, 18.07.2022.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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@article{22dd1a7a289e4c8c9f056b3cd9fb17b4,
title = "Euclid preparation: XXI. Intermediate-redshift contaminants in the search for z>6 galaxies within the Euclid Deep Survey",
abstract = "(Abridged) The Euclid mission is expected to discover thousands of z>6 galaxies in three Deep Fields, which together will cover a ~40 deg2 area. However, the limited number of Euclid bands and availability of ancillary data could make the identification of z>6 galaxies challenging. 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. 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$\leq$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 the fiducial, 28-band photometry, and fit spectral energy distributions (SEDs) to various combinations of these simulated data. Our study demonstrates that identifying z>6 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 minimized to 7% when including ultra-deep Rubin data. For UltraVISTA-like bright galaxies, we find that Euclid (I-Y)>2.8 and (Y-J)<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 (I-Y) colours. In the most optimistic 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....",
author = "{Euclid Collaboration} and {van Mierlo}, {S. E.} and Caputi, {K. I.} and M. Ashby and H. Atek and M. Bolzonella and Bowler, {R. A. A.} and G. Brammer and Conselice, {C. J.} and J. Cuby and P. Dayal and A. D{\'i}az-S{\'a}nchez and Finkelstein, {Steven L.} and H. Hoekstra and A. Humphrey and O. Ilbert and McCracken, {H. J.} and B. Milvang-Jensen and Oesch, {P. A.} and R. Pello and G. Rodighiero and M. Schirmer and S. Tof and Weaver, {J. R.} and Wilkins, {S. M.} and Willott, {C. J.} and G. Zamorani and A. Amara and N. Auricchio and M. Baldi and R. Bender and C. Bodendorf and D. Bonino and E. Branchini and M. Brescia and J. Brinchmann and S. Camera and V. Capobianco and C. Carbone and J. Carretero and M. Castellano and S. Cavuoti and A. Cimatti and R. Cledassou and G. Congedo and L. Conversi and Y. Copin and L. Corcione and F. Courbin and I. Hook",
year = "2022",
month = jul,
day = "18",
language = "English",
journal = "Astronomy and Astrophysics",
issn = "1432-0746",
publisher = "EDP Sciences",

}

RIS

TY - JOUR

T1 - Euclid preparation: XXI. Intermediate-redshift contaminants in the search for z>6 galaxies within the Euclid Deep Survey

AU - Euclid Collaboration

AU - van Mierlo, S. E.

AU - Caputi, K. I.

AU - Ashby, M.

AU - Atek, H.

AU - Bolzonella, M.

AU - Bowler, R. A. A.

AU - Brammer, G.

AU - Conselice, C. J.

AU - Cuby, J.

AU - Dayal, P.

AU - Díaz-Sánchez, A.

AU - Finkelstein, Steven L.

AU - Hoekstra, H.

AU - Humphrey, A.

AU - Ilbert, O.

AU - McCracken, H. J.

AU - Milvang-Jensen, B.

AU - Oesch, P. A.

AU - Pello, R.

AU - Rodighiero, G.

AU - Schirmer, M.

AU - Tof, S.

AU - Weaver, J. R.

AU - Wilkins, S. M.

AU - Willott, C. J.

AU - Zamorani, G.

AU - Amara, A.

AU - Auricchio, N.

AU - Baldi, M.

AU - Bender, R.

AU - Bodendorf, C.

AU - Bonino, D.

AU - Branchini, E.

AU - Brescia, M.

AU - Brinchmann, J.

AU - Camera, S.

AU - Capobianco, V.

AU - Carbone, C.

AU - Carretero, J.

AU - Castellano, M.

AU - Cavuoti, S.

AU - Cimatti, A.

AU - Cledassou, R.

AU - Congedo, G.

AU - Conversi, L.

AU - Copin, Y.

AU - Corcione, L.

AU - Courbin, F.

AU - Hook, I.

PY - 2022/7/18

Y1 - 2022/7/18

N2 - (Abridged) The Euclid mission is expected to discover thousands of z>6 galaxies in three Deep Fields, which together will cover a ~40 deg2 area. However, the limited number of Euclid bands and availability of ancillary data could make the identification of z>6 galaxies challenging. 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. 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$\leq$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 the fiducial, 28-band photometry, and fit spectral energy distributions (SEDs) to various combinations of these simulated data. Our study demonstrates that identifying z>6 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 minimized to 7% when including ultra-deep Rubin data. For UltraVISTA-like bright galaxies, we find that Euclid (I-Y)>2.8 and (Y-J)<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 (I-Y) colours. In the most optimistic 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....

AB - (Abridged) The Euclid mission is expected to discover thousands of z>6 galaxies in three Deep Fields, which together will cover a ~40 deg2 area. However, the limited number of Euclid bands and availability of ancillary data could make the identification of z>6 galaxies challenging. 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. 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$\leq$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 the fiducial, 28-band photometry, and fit spectral energy distributions (SEDs) to various combinations of these simulated data. Our study demonstrates that identifying z>6 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 minimized to 7% when including ultra-deep Rubin data. For UltraVISTA-like bright galaxies, we find that Euclid (I-Y)>2.8 and (Y-J)<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 (I-Y) colours. In the most optimistic 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....

M3 - Journal article

JO - Astronomy and Astrophysics

JF - Astronomy and Astrophysics

SN - 1432-0746

ER -