The Impact of Tomographic Redshift Bin Width Errors on Cosmological Probes

TL;DR

This paper investigates how errors in tomographic redshift bin widths affect cosmological parameter estimates, demonstrating that correcting these errors significantly alters the inferred value of S_8 in galaxy surveys.

Contribution

It provides an end-to-end analysis quantifying the impact of redshift bin width errors on cosmological inference using galaxy clustering and lensing data.

Findings

Correcting n(z) errors reduces the S_8 estimate from 0.841 to 0.739.

Systematic errors in redshift distributions can bias cosmological parameters.

Empirical correction of redshift bins significantly impacts cosmological results.

Abstract

Systematic errors in the galaxy redshift distribution $n(z)$ can propagate to systematic errors in the derived cosmology. We characterize how the degenerate effects in tomographic bin widths and galaxy bias impart systematic errors on cosmology inference using observational data from the Deep Lens Survey. For this we use a combination of galaxy clustering and galaxy-galaxy lensing. We present two end-to-end analyses from the catalogue level to parameter estimation. We produce an initial cosmological inference using fiducial tomographic redshift bins derived from photometric redshifts, then compare this with a result where the redshift bins are empirically corrected using a set of spectroscopic redshifts. We find that the derived parameter $S_8 \equiv \sigma_8 (\Omega_m/.3)^{1/2}$ goes from $.841^{+0.062}_{-.061}$ to $.739^{+.054}_{-.050}$ upon correcting the n(z) errors in the second method.