📝 SummarXiv

Abstract

Spectroscopic redshift errors, including redshift uncertainty and catastrophic failures, can bias cosmological measurements from galaxy redshift surveys at sub-percent level. We investigate their impact on full-shape clustering analysis using contaminated mock catalogs. We find that redshift uncertainty introduces a damping effect on the power spectrum. This damping is scale-dependent and absorbed by counterterms in the clustering model, keeping parameter biases below $5\%$ for the DESI survey. Catastrophic failures reduce the power spectrum amplitude by an approximately constant factor scaling with contamination rate $f_c$. While this effect is negligible for the DESI ELG populations ($f_c=1\%$), the slitless-like errors, combining redshift uncertainty with $f_c=5\%$ catastrophics, introduce significant biases in cosmological constraints. For this case, shifts from $6\%$ to $16\%$ ($\sim2.2\sigma$ level) arise in estimating the fractional growth rate $df\equiv f/f^{\rm{fid}}$ and the log primordial amplitude $\ln(10^{10} A_{s})$. Applying a correction factor $(1-f_c)^2$ on the galaxy power spectrum mitigates the bias but weakens the parameter constraints due to new degeneracies. Alternatively, fixing $f_c$ to its expected value during fitting successfully restores the unbiased posterior without loss in constraint. Our results indicate that for space-based slitless surveys such as \textit{Euclid}, an accurate estimation of $f_c$ and its incorporation into the clustering model are essential to get unbiased cosmological constraints. Extending to evolving dark energy and massive neutrino cosmologies, we find that redshift errors do not bias the dark energy properties parametrized by $w_0$ and $w_a$, but lead to slightly weaker constraints on $\sum m_\nu$.