Quantifying Photometric Redshift Errors in the Absence of Spectroscopic Redshifts
Ryan F. Quadri, Rik J. Williams

TL;DR
This paper introduces an empirical method to estimate photometric redshift uncertainties without relying on spectroscopic data, using close galaxy pairs to statistically infer redshift errors.
Contribution
It presents a novel approach leveraging galaxy pair statistics to constrain photometric redshift errors in the absence of spectroscopic redshifts.
Findings
The method accurately estimates redshift uncertainties using simulated and real data.
Close galaxy pairs provide a reliable measure of photometric redshift errors.
Systematic errors can limit the method's effectiveness.
Abstract
Much of the science that is made possible by multiwavelength redshift surveys requires the use of photometric redshifts. But as these surveys become more ambitious, and as we seek to perform increasingly accurate measurements, it becomes crucial to take proper account of the photometric redshift uncertainties. Ideally the uncertainties can be directly measured using a comparison to spectroscopic redshifts, but this may yield misleading results since spectroscopic samples are frequently small and not representative of the parent photometric samples. We present a simple and powerful empirical method to constrain photometric redshift uncertainties in the absence of spectroscopic redshifts. Close pairs of galaxies on the sky have a significant probability of being physically associated, and therefore of lying at nearly the same redshift. The difference in photometric redshifts in close…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
