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

Lazeyras, Titouan

doi:10.1088/1475-7516/2021/10/063

Cited by 22 publications

(20 citation statements)

References 105 publications

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“…2 any obvious systematic trend with the value of Λ. Perhaps the main noteworthy difference is a noticeable decrease in precision for the L box ≈ 800Mpc box with Λ = 0.1h/Mpc, suggesting that even this bigger box begins to loose some constraining power on b K 2 when this cutoff is employed (our companion paper [62] shows indeed that the signal-to-noise on b K 2 for Λ = 0.1h/Mpc is higher in a larger box with L box = 2400Mpc/h).…”

Section: Convergence Tests On the Cutoff λmentioning

confidence: 93%

“…4 show also an intriguing feature on the b K 2 (b 1 ) relation of the stellar mass selected objects at z = 2 and z = 3, which exhibits a non-monotonic dependence on b 1 that varies steeply in some b 1 intervals; this is especially noticeable for the z = 3 galaxy results (lower right panel). With just a single, relatively small-volume simulation, it is hard to rule out this as due to numerical noise, but we mention it explicitly anyway in light of the results in our companion paper [62] where similar (and higher signal-to-noise) features are also observed in halo assembly bias, i.e. when halos in gravity-only (larger-volume) simulations are selected by properties other than their total mass (namely concentration, angular momentum and shape).…”

Section: Galaxy Bias As a Function Of Simulated Galaxy Propertiesmentioning

confidence: 99%

“…[55][56][57][58] on forward models, including the derivation of the crucial likelihood function using the EFT formalism [55,60,61]. This paper is accompanied by another one using the same methodology, but focused on the assembly bias signal of b 2 and b K 2 of dark matter halos [62] (i.e. the dependence of these bias parameters on halo properties beyond their total mass).…”

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confidence: 99%

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Galaxy bias from forward models: linear and second-order bias of IllustrisTNG galaxies

Barreira,

Lazeyras,

Schmidt

2021

Preprint

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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 box = 205Mpc/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. This 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 σ 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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Section: Convergence Tests On the Cutoff λmentioning

confidence: 93%

Section: Galaxy Bias As a Function Of Simulated Galaxy Propertiesmentioning

confidence: 99%

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confidence: 99%

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Galaxy bias from forward models: linear and second-order bias of IllustrisTNG galaxies

Barreira,

Lazeyras,

Schmidt

2021

Preprint

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“…It demonstrates that PNG constraints can be significantly improved with a better knowledge of bias parameters, which motivates further work on their calibration with simulations, e.g. along the lines of [73,74].…”

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confidence: 80%

Constraints on Single-Field Inflation from the BOSS Galaxy Survey

Cabass,

Ivanov,

Philcox

et al. 2022

Preprint

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Non-local primordial non-Gaussianity (NLPNG) is a smoking gun of interactions in single-field inflationary models, and can be written as a combination of the equilateral and orthogonal templates. We present the first constraints on these from the redshift-space galaxy power spectra and bispectra of the Baryon Oscillation Spectroscopic Survey (BOSS) data. These are the first such measurements independent of the cosmic microwave background fluctuations. We perform a consistent analysis that includes all necessary nonlinear corrections generated by NLPNG, and vary all relevant cosmological and nuisance parameters in a global fit to the data. Our conservative analysis yields joint limits on the amplitudes of the equilateral and orthogonal shapes, f equil NL = 940 ± 600, f ortho NL = −170 ± 170 (both at 68% CL). These can be used to derive constraints on coefficients of the effective single-field inflationary Lagrangian; in particular, we find that the sound speed of inflaton fluctuations has the bound cs ≥ 0.013 at 95% CL. Fixing the quadratic galaxy bias and cosmological parameters, the constraints can be tightened to f equil NL = 260 ± 300, f ortho NL = −23 ± 120 (68% CL).

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“…We repeat this procedure for all the fields appearing in Eq. (2.10) (see also [44,45] for a recent study of halo and galaxy bias using this method).…”

Section: The Eft Likelihoodmentioning

confidence: 99%

BAO scale inference from biased tracers using the EFT likelihood

Babić,

Schmidt,

Tucci

2022

Preprint

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The physical scale corresponding to baryon acoustic oscillations (BAO), the size of the sound horizon at recombination, is precisely determined by CMB experiments. Measuring the apparent size of the BAO scale imprinted in the clustering of galaxies gives us a direct estimate of the angular-diameter distance and the Hubble parameter as a function of redshift. The BAO feature is damped by non-linear structure formation, which reduces the precision with which we can infer the BAO scale from standard galaxy clustering analysis methods. Many methods to undo this damping via the so-called BAO reconstruction have so far been proposed; however, they all rely on backward modeling. In this paper, we present the first results of BAO inference from rest-frame halo catalogs using forward modeling combined with the EFT likelihood, in the case where the initial phases of the density field are fixed. We show that the remaining systematic bias is less than 2% when we consider cutoff values of Λ ≤ 0.25 h Mpc −1 for all halo samples considered, and below 1% and consistent with zero for all but the most highly biased samples. We also demonstrate that, when compared to the standard power spectrum likelihood approach under the same assumption of fixed phases, the 1σ errors associated to the field level inference of the BAO scale are 1.1 to 3.3 times smaller, depending on the value of the cutoff and the halo sample. Our analysis therefore unveils another promising feature of using field-level inference for high-precision cosmology.

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

Cited by 22 publications

References 105 publications

Galaxy bias from forward models: linear and second-order bias of IllustrisTNG galaxies

Galaxy bias from forward models: linear and second-order bias of IllustrisTNG galaxies

Constraints on Single-Field Inflation from the BOSS Galaxy Survey

BAO scale inference from biased tracers using the EFT likelihood

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