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%.