Photometric Redshifts and Signal-to-Noise
V. E. Margoniner, D. M. Wittman

TL;DR
This study examines how photometric signal-to-noise ratios affect the accuracy of photometric redshift estimates in multi-band surveys, using simulations and real data to identify optimal quality cuts.
Contribution
It demonstrates that ODDS parameter cuts improve galaxy redshift precision more effectively than simple S/N thresholds across different galaxy types.
Findings
Precision degrades with decreasing S/N.
ODDS > 0.4 doubles usable galaxy count at same accuracy.
Elliptical galaxies have the tightest redshift relation.
Abstract
We investigate the impact of photometric signal-to-noise (S/N) on the precision of photometric redshifts in multi-band imaging surveys, using both simulations and real data. We simulate the optical 4-band (BVRz) Deep Lens Survey (DLS, Wittman etal 2002), and use the publicly available Bayesian Photometric Redshift code BPZ by Benitez (2000). The simulations include a realistic range of magnitudes and colors and vary from infinite S/N to S/N=5. The real data are from DLS photometry and two spectroscopic surveys, and explore a range of S/N by adding noise to initially very high S/N photometry. Precision degrades steadily as S/N drops, both because of direct S/N effects and because lower S/N is linked to fainter galaxies with a weaker magnitude prior. If a simple S/N cut were used, S/N>17 in R (corresponding, in the DLS, to lower S/N in other bands) would be required to keep the scatter in…
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