Galaxy Bias Parameter Research Articles

The renormalization group for large-scale structure: primordial non-Gaussianities

The renormalization group for large-scale structure (RG-LSS) describes the evolution of galaxy bias and stochastic parameters as a function of the cutoff Λ. In this work, we introduce interaction vertices that describe primordial non-Gaussianity into the Wilson-Polchinski framework, thereby extending the free theory to the interacting case.The presence of these interactions forces us to include new operators and bias coefficients to the bias expansion to ensure closure under renormalization.We recover the previously-derived “scale-dependent bias” contributions, as well as a new (subdominant) stochastic contribution.We derive the renormalization group equations governing the RG-LSS for a large class of interactions which account for vertices at linear order in f NL that parametrize interacting scalar and massive spinning fields during inflation.Solving the RG equations, we show the evolution of the non-Gaussian contributions to galaxy clustering as a function of scale.

Redshift evolution and covariances for joint lensing and clustering studies with DESI Y1

ABSTRACT Galaxy–galaxy lensing (GGL) and clustering measurements from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) data set promise to yield unprecedented combined-probe tests of cosmology and the galaxy–halo connection. In such analyses, it is essential to identify and characterize all relevant statistical and systematic errors. We forecast the covariances of DESI Y1 GGL + clustering measurements and the systematic bias due to redshift evolution in the lens samples. Focusing on the projected clustering and GGL correlations, we compute a Gaussian analytical covariance, using a suite of N-body and lognormal simulations to characterize the effect of the survey footprint. Using the DESI one percent survey data, we measure the evolution of galaxy bias parameters for the DESI luminous red galaxy (LRG) and bright galaxy survey (BGS) samples. We find mild evolution in the LRGs in $0.4 < z < 0.8$, subdominant to the expected statistical errors. For BGS, we find less evolution for brighter absolute magnitude cuts, at the cost of reduced sample size. We find that for a redshift bin width $\Delta z = 0.1$, evolution effects on DESI Y1 GGL is negligible across all scales, all fiducial selection cuts, all fiducial redshift bins. Galaxy clustering is more sensitive to evolution due to the bias squared scaling. Nevertheless the redshift evolution effect is insignificant for clustering above the 1-halo scale of $0.1h^{-1}$ Mpc. For studies that wish to reliably access smaller scales, additional treatment of redshift evolution is likely needed. This study serves as a reference for GGL and clustering studies using the DESI Y1 sample.

Faster cosmological analysis with power spectrum without simulations

ABSTRACT Future surveys could obtain tighter constraints on the cosmological parameters with the galaxy power spectrum than with the cosmic microwave background. However, the inclusion of multiple overlapping tracers, redshift bins, and more non-linear scales means that generating the necessary ensemble of simulations for model-fitting presents a computational burden. In this work, we combine full-shape fitting of galaxy power spectra, analytical covariance matrix estimates, the massively optimized parameter estimation and data compression (MOPED) method, and the Taylor expansion interpolation of the power spectrum for the first time to constrain the cosmological parameters directly from a state-of-the-art set of galaxy clustering measurements. We find it takes less than a day to compute the analytical covariance while it takes several months to calculate the simulated ones. Combining MOPED with the Taylor expansion interpolation of the power spectrum, we can constrain the cosmological parameters in just a few hours instead of a few days. We also find that even without a priori knowledge of the best-fitting cosmological or galaxy bias parameters, the analytical covariance matrix with the MOPED compression still gives consistent cosmological constraints to within 0.1σ after two iterations. Therefore, the pipeline we have developed here can significantly speed up the analysis for future surveys.

The Aemulus Project. VI. Emulation of Beyond-standard Galaxy Clustering Statistics to Improve Cosmological Constraints

There is untapped cosmological information in galaxy redshift surveys in the nonlinear regime. In this work, we use the Aemulus suite of cosmological N-body simulations to construct Gaussian process emulators of galaxy clustering statistics at small scales (0.1–50 h −1 Mpc) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics—the projected correlation function w p(r p), the redshift-space monopole of the correlation function ξ 0(s), and the quadrupole ξ 2(s)—we emulate statistics that include information about the local environment, namely the underdensity probability function P U(s) and the density-marked correlation function M(s). This extends the model of Aemulus III for redshift-space distortions by including new statistics sensitive to galaxy assembly bias. In recovery tests, we find that the beyond-standard statistics significantly increase the constraining power on cosmological parameters of interest: including P U(s) and M(s) improves the precision of our constraints on Ωm by 27%, σ 8 by 19%, and the growth of structure parameter, f σ 8, by 12% compared to standard statistics. We additionally find that scales below ∼6 h −1 Mpc contain as much information as larger scales. The density-sensitive statistics also contribute to constraining halo occupation distribution parameters and a flexible environment-dependent assembly bias model, which is important for extracting the small-scale cosmological information as well as understanding the galaxy–halo connection. This analysis demonstrates the potential of emulating beyond-standard clustering statistics at small scales to constrain the growth of structure as a test of cosmic acceleration.

Galaxy bias renormalization group

The effective field theory of large-scale structure allows for a consistent perturbative bias expansion of the rest-frame galaxy density field. In this work, we present a systematic approach to renormalize galaxy bias parameters using a finite cutoff scale Λ. We derive the differential equations of the Wilson-Polchinski renormalization group that describe the evolution of the finite-scale bias parameters with Λ, analogous to the β-function running in QFT. We further provide the connection between the finite-cutoff scheme and the renormalization procedure for n-point functions that has been used as standard in the literature so far; some inconsistencies in the treatment of renormalized bias in current EFT analyses are pointed out as well. The fixed-cutoff scheme allows us to predict, in a principled way, the finite part of loop contributions which is due to perturbative modes and which, in the standard renormalization approach, is absorbed into counterterms. We expect that this will allow for the robust extraction of (a yet-to-be-determined amount of) additional cosmological information from galaxy clustering, both when using field-level techniques and n-point functions.

Beyond 3×2-point cosmology: the integrated shear and galaxy 3-point correlation functions

We present the integrated 3-point correlation functions (3PCF) involving both the cosmic shear and the galaxy density fields. These are a set of higher-order statistics that describe the modulation of local 2-point correlation functions (2PCF) by large-scale features in the fields, and which are easy to measure from galaxy imaging surveys. Based on previous works on the shear-only integrated 3PCF, we develop the theoretical framework for modelling 5 new statistics involving the galaxy field and its cross-correlations with cosmic shear. Using realistic galaxy and cosmic shear mocks from simulations, we determine the regime of validity of our models based on leading-order standard perturbation theory with an MCMC analysis that recovers unbiased constraints of the amplitude of fluctuations parameter A s and the linear and quadratic galaxy bias parameters b 1 and b 2. Using Fisher matrix forecasts for a DES-Y3-like survey, relative to baseline analyses with conventional 3×2PCFs, we find that the addition of the shear-only integrated 3PCF can improve cosmological parameter constraints by 20–40%. The subsequent addition of the new statistics introduced in this paper can lead to further improvements of 10–20%, even when utilizing only conservatively large scales where the tree-level models are valid. Our results motivate future work on the galaxy and shear integrated 3PCFs, which offer a practical way to extend standard analyses based on 3×2PCFs to systematically probe the non-Gaussian information content of cosmic density fields.

Towards optimal and robust f_nl constraints with multi-tracer analyses

We discuss the potential of the multi-tracer technique to improve observational constraints of the local primordial non-Gaussianity (PNG) parameter f nl from the galaxy power spectrum. For two galaxy samples A and B, the constraining power is ∝ |bB 1 bA ϕ - bA 1 bB ϕ |, where b 1 and bϕ are the linear and PNG galaxy bias parameters. We show this allows for significantly improved constraints compared to the traditional expectation ∝ |bA - bB | based on naive universality-like relations where bϕ ∝ b 1. Using IllustrisTNG galaxy simulation data, we find that different equal galaxy number splits of the full sample lead to different |bB 1 bA ϕ - bA 1 bB ϕ |, and thus have different constraining power. Of all of the strategies explored, splitting by g-r color is the most promising, more than doubling the significance of detecting f nl bϕ ≠ 0. Importantly, since these are constraints on f nl bϕ and not f nl , they do not require priors on the bϕ (b 1) relation. For direct constraints on f nl , we show that multi-tracer constraints can be significantly more robust than single-tracer to bϕ misspecifications and uncertainties; this relaxes the precision and accuracy requirements for bϕ priors. Our results present new opportunities to improve our chances to detect and robustly constrain f nl , and strongly motivate galaxy formation simulation campaigns to calibrate the bϕ (b 1) relation.

Constraints on compensated isocurvature perturbations from BOSS DR12 galaxy data

We use the BOSS DR12 galaxy power spectrum to constrain compensated isocurvature perturbations (CIP), which are opposite-sign primordial baryon and dark matter perturbations that leave the total matter density unchanged. Long-wavelength CIP σ(x) enter the galaxy density contrast as δg (x) ⊃ bσσ(x), with bσ the linear CIP galaxy bias parameter. We parameterize the CIP spectra as Pσσ = A 2 Pℛℛ and Pσℛ = ξ√PσσPℛℛ , where A is the CIP amplitude and ξ is the correlation with the curvature perturbations ℛ. We find a significance of detection of Ab σ ≠ 0 of 1.8σ for correlated CIP (ξ = 1), consistent with no detection. For uncorrelated CIP (ξ = 0), the constraints are instead more significantly shifted away from zero, although this may be due to large-scale data systematics which have a bigger impact on these type of CIP. The constraints on A depend on the assumed priors for the bσ parameter, which we estimate using separate universe simulations. Assuming bσ values representative of all halos we find σA = 145 for correlated CIP and σ |A| = 475 for uncorrelated CIP. Our strongest uncorrelated CIP constraint is for bσ representative of the 33% most concentrated halos, σ |A| = 197, which is better than the current CMB bounds |A| ≲ 360. We also discuss the impact of the local primordial non-Gaussianity parameter f NL in CIP constraints. Our results demonstrate the power of galaxy data to place tight constraints on CIP, and motivate works to understand better the impact of data systematics, as well as to determine theory priors for bσ .

The Aemulus Project. V. Cosmological Constraint from Small-scale Clustering of BOSS Galaxies

We analyze clustering measurements of BOSS galaxies using a simulation-based emulator of two-point statistics. We focus on the monopole and quadrupole of the redshift-space correlation function, and the projected correlation function, at scales of 0.1 ∼ 60 h −1 Mpc. Although our simulations are based on wCDM with general relativity (GR), we include a scaling parameter of the halo velocity field, γ f , defined as the amplitude of the halo velocity field relative to the GR prediction. We divide the BOSS data into three redshift bins. After marginalizing over other cosmological parameters, galaxy bias parameters, and the velocity scaling parameter, we find f σ 8(z = 0.25) = 0.413 ± 0.031, f σ 8(z = 0.4) = 0.470 ± 0.026, and f σ 8(z = 0.55) = 0.396 ± 0.022. Compared with Planck observations using a flat Lambda cold dark matter model, our results are lower by 1.9σ, 0.3σ, and 3.4σ, respectively. These results are consistent with other recent simulation-based results at nonlinear scales, including weak lensing measurements of BOSS LOWZ galaxies, two-point clustering of eBOSS LRGs, and an independent clustering analysis of BOSS LOWZ. All these results are generally consistent with a combination of . We note, however, that the BOSS data is well fit assuming GR, i.e., γ f = 1. We cannot rule out an unknown systematic error in the galaxy bias model at nonlinear scales, but near-future data and modeling will enhance our understanding of the galaxy–halo connection, and provide a strong test of new physics beyond the standard model.

The time evolution of bias

ABSTRACT We investigate the time evolution of bias of cosmic density fields. We perform numerical simulations of the evolution of the cosmic web for the conventional Λ cold dark matter (ΛCDM) model. The simulations cover a wide range of box sizes $L=256\rm{-}1024\,h^{-1}\, {\rm Mpc}$, and epochs from very early moments z = 30 to the present moment z = 0. We calculate spatial correlation functions of galaxies, ξ(r), using dark matter particles of the biased Lambda cold dark mattter (ΛCDM) simulation. We analyse how these functions describe biasing properties of the evolving cosmic web. We find that for all cosmic epochs the bias parameter, defined through the ratio of correlation functions of selected samples and matter, depends on two factors: the fraction of matter in voids and in the clustered population, and the luminosity (mass) of galaxy samples. Gravity cannot evacuate voids completely, thus there is always some unclustered matter in voids, and the bias parameter of galaxies is always greater than unity, over the whole range of evolution epochs. We find that for all cosmic epochs bias parameter values form regular sequences, depending on galaxy luminosity (particle density limit), and decreasing with time.

Can we actually constrain fNL using the scale-dependent bias effect? An illustration of the impact of galaxy bias uncertainties using the BOSS DR12 galaxy power spectrum

The scale-dependent bias effect on the galaxy power spectrum is a very promising probe of the local primordial non-Gaussianity (PNG) parameter f NL, but the amplitude of the effect is proportional to f NL bϕ , where bϕ is the linear PNG galaxy bias parameter. Our knowledge of bϕ is currently very limited, yet nearly all existing f NL constraints and forecasts assume precise knowledge for it. Here, we use the BOSS DR12 galaxy power spectrum to illustrate how our uncertain knowledge of bϕ currently prevents us from constraining f NL with a given statistical precision σ fNL. Assuming different fixed choices for the relation between bϕ and the linear density bias b 1, we find that σ fNL can vary by as much as an order of magnitude. Our strongest bound is f NL = 16 ± 16 (1σ), while the loosest is f NL = 230 ± 226 (1σ) for the same BOSS data. The impact of bϕ can be especially pronounced because it can be close to zero. We also show how marginalizing over bϕ with wide priors is not conservative, and leads in fact to biased constraints through parameter space projection effects. Independently of galaxy bias assumptions, the scale-dependent bias effect can only be used to detect f NL ≠ 0 by constraining the product f NL bϕ , but the error bar σ fNL remains undetermined and the results cannot be compared with the CMB; we find f NL bϕ ≠ 0 with 1.6σ significance. We also comment on why these issues are important for analyses with the galaxy bispectrum. Our results strongly motivate simulation-based research programs aimed at robust theoretical priors for the bϕ parameter, without which we may never be able to competitively constrain f NL using galaxy data.

Cosmology with the redshift-space galaxy bispectrum monopole at one-loop order

We study the cosmological information content of the redshift-space galaxy bispectrum monopole at one-loop order in perturbation theory. We incorporate all effects necessary for comparison to data: fourth-order galaxy bias, infrared resummation (accounting for the nonlinear evolution of baryon acoustic oscillations), ultraviolet counterterms, nonlinear redshift-space distortions, stochastic contributions, projection, and binning effects. The model is implemented using FFTLog, and validated with the PT Challenge suite of $N$-body simulations, whose large volume allows for high-precision tests. Focusing on the mass fluctuation amplitude, ${\ensuremath{\sigma}}_{8}$, and galaxy bias parameters, we find that including one-loop corrections allow us to significantly extend the range of scales over which the bispectrum can be modeled, and greatly tightens constraints on bias parameters. However, this does not lead to noticeable improvements in the ${\ensuremath{\sigma}}_{8}$ error bar due to the necessary marginalization over a large number of nuisance parameters with conservative priors. Analyzing a BOSS-volume likelihood, we find that the addition of the one-loop bispectrum may lead to improvements on primordial non-Gaussianity constraints by $\ensuremath{\lesssim}30%$ and on ${\ensuremath{\sigma}}_{8}$ by $\ensuremath{\approx}10%$, though we caution that this requires pushing the analysis to short scales where the galaxy bias parameters may not be correctly recovered; this may lead to biases in the recovered parameter values. We conclude that restrictive priors from simulations or higher-order statistics such as the bispectrum multipoles will be needed in order to realize the full information content of the galaxy bispectrum.

Dark Energy Survey year 3 results: Constraints on cosmological parameters and galaxy-bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample

We constrain cosmological and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey Year-3 data. We describe our modeling framework, and choice of scales analyzed, validating their robustness to theoretical uncertainties in small-scale clustering by analyzing simulated data. Using a linear galaxy bias model and redMaGiC galaxy sample, we obtain constraints on the matter density to be $\Omega_{\rm m} = 0.325^{+0.033}_{-0.034}$. We also implement a non-linear galaxy bias model to probe smaller scales that includes parameterization based on hybrid perturbation theory and find that it leads to a 17% gain in cosmological constraining power. We perform robustness tests of our methodology pipeline and demonstrate the stability of the constraints to changes in the theoretical model. Using the redMaGiC galaxy sample as foreground lens galaxies, we find the galaxy clustering and galaxy-galaxy lensing measurements to exhibit significant signals akin to de-correlation between galaxies and mass on large scales, which is not expected in any current models. This likely systematic measurement error biases our constraints on galaxy bias and the $S_8$ parameter. We find that a scale-, redshift- and sky-area-independent phenomenological de-correlation parameter can effectively capture the impact of this systematic error. We trace the source of this de-correlation to a color-dependent photometric issue and minimize its impact on our result by changing the selection criteria of redMaGiC galaxies. Using this new sample, our constraints on the $S_8$ parameter are consistent with previous studies, and we find a small shift in the $\Omega_{\rm m}$ constraints compared to the fiducial redMaGiC sample. We constrain the mean host halo mass of the redMaGiC galaxies in this new sample to be approximately $1.6 \times 10^{13} M_{\odot}/h$.

Constraints on Single-Field Inflation from the BOSS Galaxy Survey.

Nonlocal 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 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_{NL}^{equil}=940±600 and f_{NL}^{ortho}=-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 c_{s}≥0.013 at 95%CL. Fixing the quadratic galaxy bias and cosmological parameters, the constraints can be tightened to f_{NL}^{equil}=260±300 and f_{NL}^{ortho}=-23±120 (68%CL).

Priors on Lagrangian bias parameters from galaxy formation modelling

ABSTRACT We study the relations among the parameters of the hybrid Lagrangian bias expansion model, fitting biased auto and cross power spectra up to $k_{\rm max} = 0.7 \, h \, \mathrm{Mpc}^{-1}$. We consider ∼8000 halo and galaxy samples, with different halo masses, redshifts, galaxy number densities, and varying the parameters of the galaxy formation model. Galaxy samples are obtained through state-of-the-art extended subhalo abundance matching techniques and include both stellar mass and star formation rate selected galaxies. All of these synthetic galaxy samples are publicly available. We find that the hybrid Lagrangian bias model provides accurate fits to all of our halo and galaxy samples. The coevolution relations between galaxy bias parameters, although roughly compatible with those obtained for haloes, show systematic shifts and larger scatter. We explore possible sources of this difference in terms of dependence on halo occupation and assembly bias of each sample. The bias parameter relations displayed in this work can be used as a prior for future Bayesian analyses employing the hybrid Lagrangian bias expansion model.

Constraining Brans–Dicke Cosmology with the CSST Galaxy Clustering Spectroscopic Survey

The Brans–Dicke (BD) theory is the simplest Scalar-Tensor theory of gravity, which can be considered as a candidate of modified Einstein’s theory of general relativity. In this work, we forecast the constraints on BD theory in the CSST galaxy clustering spectroscopic survey with a magnitude limit ∼23 AB mag for point-source 5σ detection. We generate mock data based on the zCOSMOS catalog and consider the observational and instrumental effects of the CSST spectroscopic survey. We predict galaxy power spectra in the BD theory from z = 0 to 1.5, and the galaxy bias and other systematical parameters are also included. The Markov Chain Monte Carlo technique is employed to find the best-fits and probability distributions of the cosmological and systematical parameters. A BD parameter ζ is introduced, which satisfies . We find that the CSST spectroscopic galaxy clustering survey can give ∣ζ∣ < 10−2, or equivalently and , under the assumption ζ = 0. These constraints are almost at the same order of magnitude compared to the joint constraints using the current cosmic microwave background, baryon acoustic oscillations and Type Ia supernova data, indicating that the CSST galaxy clustering spectroscopic survey would be powerful for constraining the BD theory and other modified gravity theories.

Probing gravity with the DES-CMASS sample and BOSS spectroscopy

ABSTRACT The DES-CMASS sample (DMASS) is designed to optimally combine the weak lensing measurements from the Dark Energy Survey (DES) and redshift-space distortions (RSD) probed by the CMASS galaxy sample from the Baryonic Oscillation Spectroscopic Survey. In this paper, we demonstrate the feasibility of adopting DMASS as the equivalent of CMASS for a joint analysis of DES and BOSS in the framework of modified gravity. We utilize the angular clustering of the DMASS galaxies, cosmic shear of the DES metacalibration sources, and cross-correlation of the two as data vectors. By jointly fitting the combination of the data with the RSD measurements from the CMASS sample and Planck data, we obtain the constraints on modified gravity parameters $\mu _0=-0.37^{+0.47}_{-0.45}$ and $\Sigma _0=0.078^{+0.078}_{-0.082}$. Our constraints of modified gravity with DMASS are tighter than those with the DES Year 1 redMaGiC sample with the same external data sets by 29 per cent for μ0 and 21 per cent for Σ0, and comparable to the published results of the DES Year 1 modified gravity analysis despite this work using fewer external data sets. This improvement is mainly because the galaxy bias parameter is shared and more tightly constrained by both CMASS and DMASS, effectively breaking the degeneracy between the galaxy bias and other cosmological parameters. Such an approach to optimally combine photometric and spectroscopic surveys using a photometric sample equivalent to a spectroscopic sample can be applied to combining future surveys having a limited overlap such as DESI and LSST.

Testing one-loop galaxy bias: Joint analysis of power spectrum and bispectrum

We present a joint likelihood analysis of the real-space power spectrum and bispectrum measured from a variety of halo and galaxy mock catalogs. A novel aspect of this work is the inclusion of nonlinear triangle configurations for the bispectrum, made possible by a complete next-to-leading order ("one-loop") description of galaxy bias, as is already common practice for the power spectrum. Based on the goodness-of-fit and the unbiasedness of the parameter posteriors, we accomplish a stringent validation of this model compared to the leading order ("tree-level") bispectrum. Using measurement uncertainties that correspond to an effective survey volume of $6\,(\mathrm{Gpc}/h)^3$, we determine that the one-loop corrections roughly double the applicable range of scales, from $\sim 0.17\,h/\mathrm{Mpc}$ (tree-level) to $\sim 0.3\,h/\mathrm{Mpc}$. This converts into a $1.5 - 2$x improvement on constraints of the linear bias parameter at fixed cosmology, and a $1.5 - 2.4$x shrinkage of uncertainties on the amplitude of fluctuations $A_s$, which clearly demonstrates the benefit of extracting information from nonlinear scales despite having to marginalize over a larger number of bias parameters. Besides, our precise measurements of galaxy bias parameters up to fourth order allow for thorough comparisons to coevolution relations, showing excellent agreement for all contributions generated by the nonlocal action of gravity. Using these relations in the likelihood analysis does not compromise the model validity and is crucial for obtaining the quoted improvements on $A_s$. We also analyzed the impact of higher-derivative and scale-dependent stochastic terms, finding that for a subset of our tracers the former can boost the performance of the tree-level model with constraints on $A_s$ that are only slightly degraded compared to the one-loop model.

Responses of Halo Occupation Distributions: a new ingredient in the halo model & the impact on galaxy bias

Halo occupation distribution (HOD) models describe the number of galaxies that reside in different haloes, and are widely used in galaxy-halo connection studies using the halo model (HM). Here, we introduce and study HOD response functions R \U0001d4aa g that describe the response of the HODs to long-wavelength perturbations \U0001d4aa. The linear galaxy bias parameters b \U0001d4aa g are a weighted version of b \U0001d4aa h + R \U0001d4aa g , where b \U0001d4aa h is the halo bias, but the contribution from R \U0001d4aa g is routinely ignored in the literature. We investigate the impact of this by measuring the R \U0001d4aa g in separate universe simulations of the IllustrisTNG model for three types of perturbations: total matter perturbations, \U0001d4aa = δ h ; baryon-CDM compensated isocurvature perturbations, \U0001d4aa = σ; and potential perturbations with local primordial non-Gaussianity, \U0001d4aa ∝ f NLϕ. Our main takeaway message is that the R \U0001d4aa g are not negligible in general and their size should be estimated on a case-by-case basis. For stellar-mass selected galaxies, the responses R \U0001d4aa g and R σ g are sizeable and cannot be neglected in HM calculations of the bias parameters b ϕ g and b σ g ; this is relevant to constrain inflation using galaxies. On the other hand, we do not detect a strong impact of the HOD response R 1 g on the linear galaxy bias b 1 g . These results can be explained by the impact that the perturbations \U0001d4aa have on stellar-to-total-mass relations. We also look into the impact on the bias of the gas distribution and find similar conclusions. We show that a single extra parameter describing the overall amplitude of R \U0001d4aa g recovers the measured b \U0001d4aa g well, which indicates that R \U0001d4aa g can be easily added to HM/HOD studies as a new ingredient.

Galaxy skew-spectra in redshift-space

Modern galaxy surveys focus on the galaxy power spectrum or 2-point correlation function to test and constrain cosmological models.Additional information comes from higher-order N-point functions, but their analysis is challenging. A simple solution is to compute the cross-power spectrum between the squared galaxy density and the galaxy density. Being simple to measure and to plot, this skew-spectrum shares many of the familiar useful properties of the standard galaxy power spectrum. We show that by computing multiple quadratic fields and correlating them with the density, all contributions to the tree-level redshift-space galaxy bispectrum can be captured with skew-spectra. Using synthetic datasets, we show that our measurement pipeline matches analytical predictions, and that their dependence on galaxy bias parameters and the logarithmic growth rate is as expected theoretically.