Assembly bias in quadratic bias parameters of dark matter halos from forward modeling

Abstract

We use the forward modeling approach to galaxy clustering combined with the likelihood from the effective-field theory of large-scale structure to measure assembly bias, i.e. the dependence of halo bias on properties beyond the total mass, in the linear ($b_1$) and second order bias parameters ($b_2$ and $b_{K^2}$) of dark matter halos in $N$-body simulations. This is the first time that assembly bias in the tidal bias parameter $b_{K^2}$ is measured. We focus on three standard halo properties: the concentration $c$, spin $\lambda$, and sphericity $s$, for which we find an assembly bias signal in $b_{K^2}$ that is opposite to that in $b_1$. Specifically, at fixed mass, halos that get more (less) positively biased in $b_1$, get less (more) negatively biased in $b_{K^2}$. We also investigate the impact of assembly bias on the $b_2(b_1)$ and $b_{K^2}(b_1)$ relations, and find that while the $b_2(b_1)$ relation stays roughly unchanged, assembly bias strongly impacts the $b_{K^2}(b_1)$ relation. This impact likely extends also to the corresponding relation for galaxies, which motivates future studies to design better priors on $b_{K^2}(b_1)$ for use in cosmological constraints from galaxy clustering data.

22 pages, 5 figures ; v2: version published in JCAP

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Cited by in corpus (1)

• A fully Lagrangian, non-parametric bias model for dark-matter halos