Taming assembly bias for primordial non-Gaussianity

Fuente: arXiv
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Main Authors: Fondi, Emanuele, Verde, Licia, Villaescusa-Navarro, Francisco, Baldi, Marco, Coulton, William R., Jung, Gabriel, Karagiannis, Dionysios, Liguori, Michele, Ravenni, Andrea, Wandelt, Benjamin D.
Format: Preprint
Published: 2023
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author Fondi, Emanuele
Verde, Licia
Villaescusa-Navarro, Francisco
Baldi, Marco
Coulton, William R.
Jung, Gabriel
Karagiannis, Dionysios
Liguori, Michele
Ravenni, Andrea
Wandelt, Benjamin D.
author_facet Fondi, Emanuele
Verde, Licia
Villaescusa-Navarro, Francisco
Baldi, Marco
Coulton, William R.
Jung, Gabriel
Karagiannis, Dionysios
Liguori, Michele
Ravenni, Andrea
Wandelt, Benjamin D.
contents Primordial non-Gaussianity of the local type induces a strong scale-dependent bias on the clustering of halos in the late-time Universe. This signature is particularly promising to provide constraints on the non-Gaussianity parameter $f_{\rm NL}$ from galaxy surveys, as the bias amplitude grows with scale and becomes important on large, linear scales. However, there is a well-known degeneracy between the real prize, the $f_{\rm NL}$ parameter, and the (non-Gaussian) assembly bias i.e., the halo formation history-dependent contribution to the amplitude of the signal, which could seriously compromise the ability of large-scale structure surveys to constrain $f_{\rm NL}$. We show how the assembly bias can be modeled and constrained, thus almost completely recovering the power of galaxy surveys to competitively constrain primordial non-Gaussianity. In particular, studying hydrodynamical simulations, we find that a proxy for the halo properties that determine assembly bias can be constructed from photometric properties of galaxies. Using a prior on the assembly bias guided by this proxy degrades the statistical errors on $f_{\rm NL}$ only mildly compared to an ideal case where the assembly bias is perfectly known. The systematic error on $f_{\rm NL}$ that the proxy induces can be safely kept under control.
format Preprint
id arxiv_https___arxiv_org_abs_2311_10088
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Taming assembly bias for primordial non-Gaussianity
Fondi, Emanuele
Verde, Licia
Villaescusa-Navarro, Francisco
Baldi, Marco
Coulton, William R.
Jung, Gabriel
Karagiannis, Dionysios
Liguori, Michele
Ravenni, Andrea
Wandelt, Benjamin D.
Cosmology and Nongalactic Astrophysics
Primordial non-Gaussianity of the local type induces a strong scale-dependent bias on the clustering of halos in the late-time Universe. This signature is particularly promising to provide constraints on the non-Gaussianity parameter $f_{\rm NL}$ from galaxy surveys, as the bias amplitude grows with scale and becomes important on large, linear scales. However, there is a well-known degeneracy between the real prize, the $f_{\rm NL}$ parameter, and the (non-Gaussian) assembly bias i.e., the halo formation history-dependent contribution to the amplitude of the signal, which could seriously compromise the ability of large-scale structure surveys to constrain $f_{\rm NL}$. We show how the assembly bias can be modeled and constrained, thus almost completely recovering the power of galaxy surveys to competitively constrain primordial non-Gaussianity. In particular, studying hydrodynamical simulations, we find that a proxy for the halo properties that determine assembly bias can be constructed from photometric properties of galaxies. Using a prior on the assembly bias guided by this proxy degrades the statistical errors on $f_{\rm NL}$ only mildly compared to an ideal case where the assembly bias is perfectly known. The systematic error on $f_{\rm NL}$ that the proxy induces can be safely kept under control.
title Taming assembly bias for primordial non-Gaussianity
topic Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2311.10088