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Register a new userGalaxy bias from forward models: linear and second-order bias of IllustrisTNG galaxies
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We use field-level forward models of galaxy clustering and the EFT likelihood formalism to study, for the first time for self-consistently simulated galaxies, the relations between the linear $b_1$ and second-order bias parameters $b_2$ and $b_{K^2}$. The forward models utilize all of the information available in the galaxy distribution up to a given order in perturbation theory, which allows us to infer these bias parameters with high signal-to-noise, even from relatively small volumes ($L_{rm box} = 205{rm Mpc}/h$). We consider galaxies from the IllustrisTNG simulations, and our main result is that the $b_2(b_1)$ and $b_{K^2}(b_1)$ relations obtained from gravity-only simulations for total mass selected objects are broadly preserved for simulated galaxies selected by stellar mass, star formation rate, color and black hole accretion rate. We also find good agreement between the bias relations of the simulated galaxies and a number of recent estimates for observed galaxy samples. The consistency under different galaxy selection criteria suggests that theoretical priors on these bias relations may be used to improve cosmological constraints based on observed galaxy samples. We do identify some small differences between the bias relations in the hydrodynamical and gravity-only simulations, which we show can be linked to the environmental dependence of the relation between galaxy properties and mass. We also show that the EFT likelihood recovers the value of $sigma_8$ to percent-level from various galaxy samples (including splits by color and star formation rate) and after marginalizing over 8 bias parameters. This demonstration using simulated galaxies adds to previous works based on halos as tracers, and strengthens further the potential of forward models to infer cosmology from galaxy data.
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We study the impact that large-scale perturbations of (i) the matter density and (ii) the primordial gravitational potential with local primordial non-Gaussianity (PNG) have on galaxy formation using the IllustrisTNG model. We focus on the linear galaxy bias $b_1$ and the coefficient $b_phi$ of the scale-dependent bias induced by PNG, which describe the response of galaxy number counts to these two types of perturbations, respectively. We perform our study using separate universe simulations, in which the effect of the perturbations is mimicked by changes to the cosmological parameters: modified cosmic matter density for $b_1$ and modified amplitude $mathcal{A}_s$ of the primordial scalar power spectrum for $b_phi$. We find that the widely used universality relation $b_phi = 2delta_c(b_1 - 1)$ is a poor description of the bias of haloes and galaxies selected by stellar mass $M_*$, which is instead described better by $b_phi(M_*) = 2delta_c(b_1(M_*) - p)$ with $p in [0.4, 0.7]$. This is explained by the different impact that matter overdensities and local PNG have on the median stellar-to-halo-mass relation. A simple model of this impact allows us to describe the stellar mass dependence of $b_1$ and $b_phi$ fairly well. Our results also show a nontrivial relation between $b_1$ and $b_phi$ for galaxies selected by color and black hole mass accretion rate. Our results provide refined priors on $b_phi$ for local PNG constraints and forecasts using galaxy clustering. Given that the widely used universality relation underpredicts $b_phi(M_*)$, existing analyses may underestimate the true constraining power on local PNG.
We discuss the question of gauge choice when analysing relativistic density perturbations at second order. We compare Newtonian and General Relativistic approaches. Some misconceptions in the recent literature are addressed. We show that the comoving-synchronous gauge is the unique gauge in General Relativity that corresponds to the Lagrangian frame and is entirely appropriate to describe the matter overdensity at second order. The comoving-synchronous gauge is the simplest gauge in which to describe Lagrangian bias at second order.
In this work, we compare large scale structure observables for stellar mass selected samples at $z=0$, as predicted by two galaxy models, the hydrodynamical simulation IllustrisTNG and the Santa-Cruz semi-analytic model (SC-SAM). Although both models have been independently calibrated to match observations, rather than each other, we find good agreement between the two models for two-point clustering and galaxy assembly bias signatures. The models also show a qualitatively similar response of occupancy and clustering to secondary halo paramaters other than mass, such as formation history and concentration, although with some quantitative differences. Thus, our results demonstrate that the galaxy-halo relationships in SC-SAM and TNG are quite similar to first order. However, we also find areas in which the models differ. For example, we note a strong correlation between halo gas content and environment in TNG, which is lacking in the SC-SAM, as well as differences in the occupancy predictions for low-mass haloes. Moreover, we show that higher-order statistics, such as cumulants of the density field, help to accurately describe the galaxy distribution and discriminate between models that show degenerate behavior for two-point statistics. Our results suggest that SAMs are a promising cost-effective and intuitive method for generating mock catalogues for next generation cosmological surveys.
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.
We model the large-scale linear galaxy bias $b_g(x,z)$ as a function of redshift $z$ and observed absolute magnitude threshold $x$ for broadband continuum emission from the far infrared to ultra-violet, as well as for prominent emission lines, such as the H$alpha$, H$beta$, Lya and [OII] lines. The modelling relies on the semi-analytic galaxy formation model GALFORM, run on the state-of-the-art $N$-body simulation SURFS with the Planck 2015 cosmology. We find that both the differential bias at observed absolute magnitude $x$ and the cumulative bias for magnitudes brighter than $x$ can be fitted with a five-parameter model: $b_g(x,z)=a + b(1+z)^e(1 + exp{[(x-c)d]})$. We also find that the bias for the continuum bands follows a very similar form regardless of wavelength due to the mixing of star-forming and quiescent galaxies in a magnitude limited survey. Differences in bias only become apparent when an additional colour separation is included, which suggest extensions to this work could look at different colours at fixed magnitude limits. We test our fitting formula against observations, finding reasonable agreement with some measurements within $1sigma$ statistical uncertainties, and highlighting areas of improvement. We provide the fitting parameters for various continuum bands, emission lines and intrinsic galaxy properties, enabling a quick estimation of the linear bias in any typical survey of large-scale structure.
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