Taming assembly bias for primordial non-Gaussianity
Emanuele FondiLicia VerdeFrancisco Villaescusa-NavarroMarco BaldiWilliam R. CoultonGabriel JungDionysios KaragiannisMichele LiguoriAndrea RavenniBenjamin D. Wandelt
Emanuele FondiLicia VerdeFrancisco Villaescusa-Navarro
...+6
Benjamin D. Wandelt
Nov 2023
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摘要原文
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.
