The effect of quasar redshift errors on Lyman-$\alpha$ forest correlation functions

TL;DR

This study investigates how errors in quasar redshift estimates affect the measurement of Lyman-alpha forest correlation functions, revealing smearing of BAO features and unphysical small-scale correlations.

Contribution

It quantifies the impact of Gaussian redshift errors on Lyman-alpha correlation functions using synthetic data from DESI, highlighting specific distortions and contaminations.

Findings

BAO feature smearing in radial direction due to redshift errors

Negligible shift in BAO peak position

Unphysical small-scale correlations increase with error amplitude

Abstract

Using synthetic Lyman-$\alpha$ forests from the Dark Energy Spectroscopic Instrument (DESI) survey, we present a study of the impact of errors in the estimation of quasar redshift on the Lyman-$\alpha$ correlation functions. Estimates of quasar redshift have large uncertainties of a few hundred $\text{km s}^{-1}\,$ due to the broadness of the emission lines and the intrinsic shifts from other emission lines. We inject Gaussian random redshift errors into the mock quasar catalogues, and measure the auto-correlation and the Lyman-$\alpha$-quasar cross-correlation functions. We find a smearing of the BAO feature in the radial direction, but changes in the peak position are negligible. However, we see a significant unphysical correlation for small separations transverse to the line of sight which increases with the amplitude of the redshift errors. We interpret this contamination as a result of the broadening of emission lines in the measured mean continuum, caused by quasar redshift errors, combined with the unrealistically strong clustering of the simulated quasars on small scales.