Taming assembly bias for primordial non-Gaussianity

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 NL from galaxy surveys, as the bias amplitude grows with scale a...

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Bibliographic Details
Published in:Journal of cosmology and astroparticle physics 2024-02, Vol.2024 (2), p.48
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: Article
Language:English
Subjects:
Amplitudes
Assembly
Bias
Clustering
Constraints
cosmological parameters from LSS
cosmological simulations
Galaxies
galaxy surveys
inflation
Large scale structure of the universe
Parameters
Systematic errors
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Summary: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 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 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 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 NL only mildly compared to an ideal case where the assembly bias is perfectly known. The systematic error on f NL that the proxy induces can be safely kept under control.
ISSN:1475-7516
1475-7516
DOI:10.1088/1475-7516/2024/02/048