Potential contamination from low/intermediate-redshift galaxies, such as objects with a prominent Balmer break, affects the photometric selection of high-redshift galaxies through identification of a Lyman break. Traditionally, contamination is estimated from spectroscopic follow-up and/or simulations. Here, we introduce a novel approach to estimating contamination for Lyman-break galaxy (LBG) samples based on measuring spatial correlation with the parent population of lower redshift interlopers. We propose two conceptual approaches applicable to different survey strategies: a single large contiguous field and a survey consisting of multiple independent lines of sight. For a large single field, we compute the cross-correlation function between galaxies at redshift z ~ 6 and intermediate-redshift galaxies at z ~ 1.3. We apply the method to the CANDELS GOODS-S and XDF surveys and compare the measurement with simulated mock observations, finding that the contamination level in both cases is not measurable and lies below $5.5%$ (at $90%$ confidence). For random-pointing multiple field surveys, we measure instead the number count correlation between high-redshift galaxies and interlopers, as a two-point correlation analysis is not generally feasible. We show an application to the LBG samples at redshift z ~ 8 and the possible interloper population at z ~ 2 in the Brightest of Reionizing Galaxies (BoRG) survey. By comparing the Pearson correlation coefficient with the result from Monte Carlo simulations, we estimate a contamination fraction of 62⁺¹³₋₃₉%, consistent with previous estimates in the literature. These results validate the proposed approach and demonstrate its utility as an independent check of contamination in photometrically selected samples of high-redshift galaxies.
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Hilmi et al. (2024) studied this question.
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