Beyond Linear Bias Expansions for AbacusSummit Halos at z = 8

TL;DR

This study investigates the non-Gaussian clustering of high-redshift halos at z=8, finding that linear and quadratic bias terms suffice to model the data, with minimal need for tidal bias terms.

Contribution

It demonstrates that only linear and quadratic bias parameters are necessary for modeling high-redshift halo clustering, challenging the need for higher-order bias terms.

Findings

Clustering modeled with linear and quadratic bias parameters.

Tidal bias not significantly detected at z=8.

Bias evolution from z=8 to z=5 follows linear trends.

Abstract

We study the non-Gaussianity of the large-scale clustering of high-redshift halos, seeking to assess which terms of standard bias expansions are needed to understand these highly biased populations. We find that the clustering can be well modeled with only linear and quadratic bias parameters while assuming a Gaussian underlying matter field. Our analysis focuses on AbacusSummit halos at redshift $z=8$. We work with halos of mass at least $1\times10^{11}h^{-1}M_\odot$ in boxes of side length $2h^{-1}$Gpc. Measurements of bias coefficients are made by fitting bias expansions to the halo power spectrum and bispectrum. Tidal bias is not detected with only a ~$0.1\sigma$ deviation from $0$, but we see a $17\sigma$ level detection for a bias term of the form $\delta^2$. A bias term of the form $\delta^3$ is weakly detected at the $1.3\sigma$ level. Nonlinear matter is also detected at a $1.3\sigma$ level. To test how bias evolves, we run one test at $z=5$. We use a mass threshold for halos that gives the same variance in the halo field as our $z=8$ sample. Bias is smaller at $z=5$ and a tidal bias is detected at the $1\sigma$ level. Bias coefficients at $z=5$ match a linear evolution of the $z=8$ bias coefficients to within $10\%$.