Primordial non-Gaussianity systematics from redshift mismatch with SPHEREx

TL;DR

This paper investigates how redshift bin mismatch in SPHEREx galaxy surveys can cause significant systematic errors in primordial non-Gaussianity measurements and proposes a scattering matrix method to correct for this bias.

Contribution

It introduces a scattering matrix formalism to mitigate redshift bin mismatch systematics in primordial non-Gaussianity estimation from SPHEREx data.

Findings

Redshift bin mismatch can cause up to 6σ bias in $f_{NL}^{loc}$ estimates.

Galaxy bias estimates can be biased by up to 12σ due to redshift misclassification.

The proposed scattering matrix method effectively reduces systematic biases in parameter estimation.

Abstract

The ability to differentiate between different models of inflation through the imprint of primordial non-Gaussianity (PNG) requires stringent constraints on the local PNG parameter $f_{\text{NL}}^{\text{loc}}$. Upcoming data from the large scale structure surveys like \textit{Euclid}, Vera C. Rubin Observatory, and the Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer (SPHEREx) will be instrumental in advancing our understanding of the inflationary epoch. In this context, we present forecasts on PNG with tomographic angular power spectra derived from simulations of SPHEREx. We put forward the effects of redshift bin mismatch of galaxies as a significant source of systematic uncertainty in the estimation of both $f_{\text{NL}}^{\text{loc}}$ and galaxy linear halo bias. We simulate $500$ SPHEREx-like galaxy density fields, and divide the galaxies into redshift bins assuming Gaussian photometric redshift errors. We show that the misclassification of galaxies in redshift bins can result in strong apparent tensions on $f_{\text{NL}}^{\text{loc}}$ up to $\sim 3-6\sigma$ and up to $\sim 9-12\sigma$ on galaxy bias. To address this, we propose a scattering matrix formalism that mitigates bin mismatch of galaxies and enables unbiased estimation of cosmological parameters from tomographic angular clustering measurements.