Kavli Affiliate: James J. Bock
| First 5 Authors: Zhaoyu Huai, Zhaoyu Huai, , ,
| Summary:
We model the impact of source confusion on photometry and the resulting
spectrophotometric redshifts for SPHEREx, a NASA Medium-Class Explorer that is
carrying out an all-sky near-infrared spectral survey. Spectral confusion from
untargeted background galaxies degrades sensitivity and introduces a spectral
bias. Using interpolated spectral energy distributions (SEDs) from the
COSMOS2020 catalog, we construct a Monte Carlo library of confusion spectra
that captures the cumulative impact from faint galaxies. By injecting confusion
realizations into galaxy SEDs and performing forced photometry at known source
positions, we quantify photometric and redshift error and bias. For our current
expected selection of sources for the cosmology analysis, we find typical
1-$sigma$ confusion levels range from $0.8-3.8 mumathrmJy$ across
$0.75-5.0 mumathrmm$. While negligible at full-sky survey depth, spectral
confusion becomes significant in the SPHEREx deep fields, reducing the number
of intermediate-precision redshifts and inducing a small systematic
overestimation in redshift. In parallel, we also model targeted source blending
from beam overlaps, which contributes additional photometric noise without
systematic redshift bias, provided that positions are known exactly. Together,
confusion and blending vary with the depth of the selected reference sample,
revealing a trade-off, where deeper selections reduce confusion but increase
blending-induced noise. Our methodology informs optimization of the SPHEREx
deep-field selection strategy and future treatments of stellar source blending
and confusion.
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