# Constraint of Void Bias on Primordial non-Gaussianity

## TL;DR

This paper investigates how cosmic voids' large-scale bias, influenced by primordial non-Gaussianity, can improve constraints on PNG parameters, showing voids provide complementary and enhanced information beyond halos.

## Contribution

It demonstrates that void bias exhibits scale-dependent corrections similar to halos and that including voids improves PNG constraints by a factor of two.

## Key findings

- Void bias shows scale dependence similar to halos.
- Large voids anti-correlate with dark matter density.
- Including voids tightens PNG parameter constraints by a factor of two.

## Abstract

We study the large-scale bias parameter of cosmic voids with primordial non-Gaussian (PNG) initial conditions of the local type. In this scenario, the dark matter halo bias exhibits a characteristic scale dependence on large scales, which has been recognized as one of the most promising probes of the local PNG. Using a suite of $N$-body simulations with Gaussian and non-Gaussian initial conditions, we find that the void bias features scale-dependent corrections on large scales, similar to its halo counterpart. We find excellent agreement between the numerical measurement of the PNG void bias and the general peak-background split prediction. Contrary to halos, large voids anti-correlate with the dark matter density field, and the large-scale Gaussian void bias ranges from positive to negative values depending on void size and redshift. Thus, the information in the clustering of voids can be complementary to that of the halos. Using the Fisher matrix formalism for multiple tracers, we demonstrate that including the scale-dependent bias information from voids, constraints on the PNG parameter $f_{\rm NL}$ can be tightened by a factor of two compared to the accessible information from halos alone, when the sampling density of tracers reaches $4 \times 10^{-3} \, h^3 \mathrm{Mpc}^{-3} $.