The local PNG bias of neutral Hydrogen, ${\rm H_I}$

TL;DR

This study uses simulations to accurately predict the local primordial non-Gaussianity bias parameters of neutral hydrogen, revealing that previous models overestimate their relation to density bias and highlighting their epoch-dependent sensitivity to $f_{NL}$.

Contribution

The paper provides the first simulation-based predictions of ${ m H_I}$ local PNG bias parameters, challenging the universality assumption and refining the understanding of their evolution and impact on $f_{NL}$ constraints.

Findings

${ m H_I}$ power spectrum sensitivity to $f_{NL}$ varies with redshift.

Universality-based models overpredict the bias relations.

Physical effects like star formation and feedback influence ${ m H_I}$ bias.

Abstract

We use separate universe simulations with the IllustrisTNG galaxy formation model to predict the local PNG bias parameters $b_\phi$ and $b_{\phi\delta}$ of atomic neutral hydrogen, ${\rm H_I}$. These parameters and their relation to the linear density bias parameter $b_1$ play a key role in observational constraints of the local PNG parameter $f_{\rm NL}$ using the ${\rm H_I}$ power spectrum and bispectrum. Our results show that the popular calculation based on the universality of the halo mass function overpredicts the $b_\phi(b_1)$ and $b_{\phi\delta}(b_1)$ relations measured in the simulations. In particular, our results show that at $z \lesssim 1$ the ${\rm H_I}$ power spectrum is more sensitive to $f_{\rm NL}$ compared to previously thought ($b_\phi$ is more negative), but is less sensitive at other epochs ($b_\phi$ is less positive). We discuss how this can be explained by the competition of physical effects such as that large-scale gravitational potentials with local PNG (i) accelerate the conversion of hydrogen to heavy elements by star formation, (ii) enhance the effects of baryonic feedback that eject the gas to regions more exposed to ionizing radiation, and (iii) promote the formation of denser structures that shield the ${\rm H_I}$ more efficiently. Our numerical results can be used to revise existing forecast studies on $f_{\rm NL}$ using 21cm line-intensity mapping data. Despite this first step towards predictions for the local PNG bias parameters of ${\rm H_I}$, we emphasize that more work is needed to assess their sensitivity on the assumed galaxy formation physics and ${\rm H_I}$ modeling strategy.