Clustering Amplitude Research Articles

Cosmological inference from an emulator based halo model. II. Joint analysis of galaxy-galaxy weak lensing and galaxy clustering from HSC-Y1 and SDSS

We present high-fidelity cosmology results from a blinded joint analysis of galaxy-galaxy weak lensing (ΔΣ) and projected galaxy clustering (wp) measured from the Hyper Suprime-Cam Year-1 (HSC-Y1) data and spectroscopic Sloan Digital Sky Survey (SDSS) galaxy catalogs in the redshift range 0.15<z<0.7. We define luminosity-limited samples of SDSS galaxies to serve as the tracers of wp in three spectroscopic redshift bins, and as the lens samples for ΔΣ. For the ΔΣ measurements, we select a single sample of 4×106 source galaxies over 140 deg2 from HSC-Y1 with photometric redshifts (photo z) greater than 0.75, enabling a better handle of photo-z errors by comparing the ΔΣ amplitudes for the three lens redshift bins. The deep, high-quality HSC-Y1 data enable significant detections of the ΔΣ signals, with integrated signal-to-noise ratio S/N∼15 in the range 3≤R/[h−1 Mpc]≤30 for the three lens samples, despite the small area coverage. For cosmological parameter inference, we use an input galaxy-halo connection model built on the dark emulator package (which uses an ensemble set of high-resolution N-body simulations and enables fast, accurate computation of the clustering observables) with a halo occupation distribution that includes nuisance parameters to marginalize over modeling uncertainties. We model the ΔΣ and wp measurements on scales from R≃3 and 2 h−1 Mpc, respectively, up to 30 h−1 Mpc (therefore excluding the baryon acoustic oscillations information) assuming a flat ΛCDM cosmology, marginalizing over about 20 nuisance parameters and demonstrating the robustness of our results to them. With various tests using mock catalogs described in Miyatake et al. [preceding paper, Phys. Rev. D 106, 083519 (2022)], we show that any bias in the clustering amplitude S8≡σ8(Ωm/0.3)0.5 due to uncertainties in the galaxy-halo connection is less than ∼50% of the statistical uncertainty of S8, unless the assembly biaseffect is unexpectedly large. Our best-fit models have S8=0.795−0.042+0.049 (mode and 68% credible interval) for the flat ΛCDM model; we find tighter constraints on the quantity S8(α=0.17)≡σ8(Ωm/0.3)0.17=0.745−0.031+0.039.23 MoreReceived 29 November 2021Accepted 22 August 2022DOI:https://doi.org/10.1103/PhysRevD.106.083520© 2022 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasCosmologyDark energyGravitational lensesGravitation, Cosmology & Astrophysics

The H α luminosity and stellar mass dependent clustering of star-forming galaxies at 0.7 &amp;lt; z &amp;lt; 1.5 with 3D-HST

ABSTRACT We present measurements of the dependence of the clustering amplitude of galaxies on their star formation rate (SFR) and stellar mass (M*) at 0.7 &amp;lt; z &amp;lt; 1.5 to assess the extent to which environment affects these properties. While these relations are well determined in the local Universe, they are much more poorly known at earlier times. For this analysis, we make use of the near-infrared HST WFC3 grism spectroscopic data in the five CANDELS fields obtained as part of the 3D-HST survey. We make projected two-point correlation function measurements using ∼6000 galaxies with accurate redshifts, M*, and H α luminosities. We find a strong dependence of clustering amplitude on H α luminosity and thus SFR. However, at fixed M*, the clustering dependence on H α luminosity is largely eliminated. We model the clustering of these galaxies within the halo occupation distribution framework using the conditional luminosity function model and the newly developed conditional stellar mass and H α luminosity distribution model. These show that galaxies with higher SFRs tend to live in higher mass haloes, but this is largely driven by the relationship between SFR and M*. Finally, we show that the small residual correlation between clustering amplitude and H α luminosity at fixed M* is likely being driven by a broadening of the SFR–M* relationship for satellite galaxies.

COMAP Early Science. V. Constraints and Forecasts at z ∼ 3

We present the current state of models for the z ∼ 3 carbon monoxide (CO) line intensity signal targeted by the CO Mapping Array Project (COMAP) Pathfinder in the context of its early science results. Our fiducial model, relating dark matter halo properties to CO luminosities, informs parameter priors with empirical models of the galaxy–halo connection and previous CO (1–0) observations. The Pathfinder early science data spanning wavenumbers k = 0.051–0.62 Mpc−1 represent the first direct 3D constraint on the clustering component of the CO (1–0) power spectrum. Our 95% upper limit on the redshift-space clustering amplitude A clust ≲ 70 μK2 greatly improves on the indirect upper limit of 420 μK2 reported from the CO Power Spectrum Survey (COPSS) measurement at k ∼ 1 Mpc−1. The COMAP limit excludes a subset of models from previous literature and constrains interpretation of the COPSS results, demonstrating the complementary nature of COMAP and interferometric CO surveys. Using line bias expectations from our priors, we also constrain the squared mean line intensity–bias product, ≲ 50 μK2, and the cosmic molecular gas density, ρ H2 < 2.5 × 108 M ⊙ Mpc−3 (95% upper limits). Based on early instrument performance and our current CO signal estimates, we forecast that the 5 yr Pathfinder campaign will detect the CO power spectrum with overall signal-to-noise ratio of 9–17. Between then and now, we also expect to detect the CO–galaxy cross-spectrum using overlapping galaxy survey data, enabling enhanced inferences of cosmic star formation and galaxy evolution history.

Cosmological analysis of three-dimensional BOSS galaxy clustering and Planck CMB lensing cross correlations via Lagrangian perturbation theory

We present a formalism for jointly fitting pre- and post-reconstruction redshift-space clustering (RSD) and baryon acoustic oscillations (BAO) plus gravitational lensing (of the CMB) that works directly with the observed 2-point statistics. The formalism is based upon (effective) Lagrangian perturbation theory and a Lagrangian bias expansion, which models RSD, BAO and galaxy-lensing cross correlations within a consistent dynamical framework. As an example we present an analysis of clustering measured by the Baryon Oscillation Spectroscopic Survey in combination with CMB lensing measured by Planck. The post-reconstruction BAO strongly constrains the distance-redshift relation, the full-shape redshift-space clustering constrains the matter density and growth rate, and CMB lensing constrains the clustering amplitude. Using only the redshift space data we obtain Ωm = 0.303 ± 0.008, H 0 = 69.21 ± 0.78 and σ 8 = 0.743 ± 0.043. The addition of lensing information, even when restricted to the Northern Galactic Cap, improves constraints to Ωm = 0.303 ± 0.008, H 0 = 69.21 ± 0.77 and σ 8 = 0.707 ± 0.035, in tension with CMB and cosmic shear constraints. The combination of Ωm and H 0 are consistent with Planck, though their constraints derive mostly from redshift-space clustering. The low σ 8 value are driven by cross correlations with CMB lensing in the low redshift bin (z ≃ 0.38) and at large angular scales, which show a 20% deficit compared to expectations from galaxy clustering alone. We conduct several systematics tests on the data and find none that could fully explain these tensions.

Evolution mapping: a new approach to describe matter clustering in the non-linear regime

ABSTRACT We present a new approach to describe statistics of the non-linear matter density field that exploits a degeneracy in the impact of different cosmological parameters on the linear dimensionless matter power spectrum, $\Delta ^2_{\rm L}(k)$. We classify all cosmological parameters into two groups, shape parameters, which determine the shape of $\Delta ^2_{\rm L}(k)$, and evolution parameters, which only affect its amplitude at any given redshift. With this definition, the time evolution of $\Delta ^2_{\rm L}(k)$ in models with identical shape parameters but different evolution parameters can be mapped from one to the other by relabelling the redshifts that correspond to the same clustering amplitude, which we characterize by the linear mass fluctuation in spheres of radius $12\, {\rm Mpc}$, σ12(z). We use N-body simulations to show that the same evolution-mapping relation gives a good description of the non-linear power spectrum, the halo mass function, or the full density field. The deviations from the exact degeneracy are the result of the different structure formation histories experienced by each model to reach the same clustering amplitude and can be accurately described in terms of differences in the suppression factor g(a) = D(a)/a. These relations can be used to drastically reduce the number of parameters required to describe the cosmology dependence of the power spectrum. We show how this can help to speed up the inference of parameter constraints from cosmological observations. We also present a new design of an emulator of the non-linear power spectrum whose predictions can be adapted to an arbitrary choice of evolution parameters and redshift.

Galaxy luminosity function pipeline for cosmology and astrophysics

Observations of high-redshift galaxies have provided us with a rich tool to study the physics at play during the epoch of reionization. The luminosity function (LF) of these objects is an indirect tracer of the complex processes that govern galaxy formation, including those of the first dark-matter structures. In this work, we present an extensive analysis of the UV galaxy LF at high redshifts to extract cosmological and astrophysical parameters. We provide a number of phenomenological approaches in modeling the UV LF and take into account various sources of uncertainties and systematics in our analysis, including cosmic variance, dust extinction, scattering in the halo-galaxy connection, and the Alcock-Paczy\ifmmode \acute{n}\else \'{n}\fi{}ski effect. Using UV LF measurements from the Hubble Space Telescope together with external data on the matter density, we derive the large-scale matter clustering amplitude to be ${\ensuremath{\sigma}}_{8}={0.76}_{\ensuremath{-}0.14}^{+0.12}$, after marginalizing over the unknown astrophysical parameters. We find that with current data this result is only weakly sensitive to our choice of astrophysical modeling, as well as the calibration of the underlying halo mass function. As a cross check, we run our analysis pipeline with mock data from the IllustrisTNG hydrodynamical simulations and find consistent results with their input cosmology. In addition, we perform a simple forecast for future space telescopes, where an improvement of roughly 30% upon our current result is expected. Finally, we obtain constraints on astrophysical parameters and the halo-galaxy connection for the models considered here. All methods discussed in this work are implemented in the form of a versatile likelihood code, gallumi, which we make public.

Cosmic Near-infrared Background Tomography with SPHEREx Using Galaxy Cross-correlations

Abstract The extragalactic background light (EBL) consists of integrated light from all sources of emission throughout the history of the universe. At near-infrared wavelengths, the EBL is dominated by stellar emission across cosmic time; however, the spectral and redshift information of the emitting sources is entangled and cannot be directly measured by absolute photometry or fluctuation measurements. Cross-correlating near-infrared maps with tracers of known redshift enables EBL redshift tomography, as EBL emission will only correlate with external tracers from the same redshift. Here, we forecast the sensitivity of probing the EBL spectral energy distribution as a function of redshift by cross-correlating the upcoming near-infrared spectro-imaging survey, SPHEREx, with several current and future galaxy redshift surveys. Using a model galaxy luminosity function, we estimate the cross power spectrum clustering amplitude on large scales, and forecast that the near-infrared EBL spectrum can be detected tomographically out to z ∼ 6. We also predict a high-significance measurement (∼102–104 σ) of the small-scale cross power spectrum out to z ∼ 10. The amplitudes of the large-scale cross power spectra can constrain the cosmic evolution of the stellar synthesis process through both continuum and the line emission, while on the nonlinear and Poisson noise scales, the high-sensitivity measurements can probe the mean spectra associated with the tracer population across redshift.

Dark Energy Survey Year 3 results: Cosmology from cosmic shear and robustness to data calibration

This work, together with its companion paper, Secco and Samuroff et al. (2021), presents the Dark Energy Survey Year 3 cosmic shear measurements and cosmological constraints based on an analysis of over 100 million source galaxies. With the data spanning 4143 deg$^2$ on the sky, divided into four redshift bins, we produce the highest significance measurement of cosmic shear to date, with a signal-to-noise of 40. We conduct a blind analysis in the context of the $\Lambda$CDM model and find a 3% constraint of the clustering amplitude, $S_8\equiv \sigma_8 (\Omega_{\rm m}/0.3)^{0.5} = 0.759^{+0.025}_{-0.023}$. A $\Lambda$CDM-Optimized analysis, which safely includes smaller scale information, yields a 2% precision measurement of $S_8= 0.772^{+0.018}_{-0.017}$ that is consistent with the fiducial case. The two low-redshift measurements are statistically consistent with the Planck Cosmic Microwave Background result, however, both recovered $S_8$ values are lower than the high-redshift prediction by $2.3\sigma$ and $2.1\sigma$ ($p$-values of 0.02 and 0.05), respectively. The measurements are shown to be internally consistent across redshift bins, angular scales and correlation functions. The analysis is demonstrated to be robust to calibration systematics, with the $S_8$ posterior consistent when varying the choice of redshift calibration sample, the modeling of redshift uncertainty and methodology. Similarly, we find that the corrections included to account for the blending of galaxies shifts our best-fit $S_8$ by $0.5\sigma$ without incurring a substantial increase in uncertainty. We examine the limiting factors for the precision of the cosmological constraints and find observational systematics to be subdominant to the modeling of astrophysics. Specifically, we identify the uncertainties in modeling baryonic effects and intrinsic alignments as the limiting systematics.

Dark Energy Survey Year 3 Results: Galaxy mock catalogs for BAO analysis

The calibration and validation of scientific analysis in simulations is a fundamental tool to ensure unbiased and robust results in observational cosmology. In particular, mock galaxy catalogs are a crucial resource to achieve these goals in the measurement of baryon acoustic oscillation (BAO) in the clustering of galaxies. Here we present a set of 1952 galaxy mock catalogs designed to mimic the Dark Energy Survey Year 3 BAO sample over its full photometric redshift range 0.6 &lt; zphoto &lt; 1.1. The mocks are based upon 488 ICE-COLA fastN-body simulations of full-sky light cones and were created by populating halos with galaxies, using a hybrid halo occupation distribution – halo abundance matching model. This model has ten free parameters, which were determined, for the first time, using an automatic likelihood minimization procedure. We also introduced a novel technique to assign photometric redshift for simulated galaxies, following a two-dimensional probability distribution with VIMOS Public Extragalactic Redshift Survey data. The calibration was designed to match the observed abundance of galaxies as a function of photometric redshift, the distribution of photometric redshift errors, and the clustering amplitude on scales smaller than those used for BAO measurements. An exhaustive analysis was done to ensure that the mocks reproduce the input properties. Finally, mocks were tested by comparing the angular correlation functionw(θ), angular power spectrumCℓ, and projected clusteringξp(r⊥) to theoretical predictions and data. The impact of volume replication in the estimate of the covariance is also investigated. The success in accurately reproducing the photometric redshift uncertainties and the galaxy clustering as a function of redshift render this mock creation pipeline as a benchmark for future analyses of photometric galaxy surveys.

Small-scale clumping at recombination and the Hubble tension

Despite the success of the standard $\Lambda$CDM model of cosmology, recent data improvements have made tensions emerge between low- and high-redshift observables, most importantly in determinations of the Hubble constant $H_0$ and the (rescaled) clustering amplitude $S_8$. The high-redshift data, from the cosmic microwave background (CMB), crucially relies on recombination physics for its interpretation. Here we study how small-scale baryon inhomogeneities (i.e., clumping) can affect recombination and consider whether they can relieve both the $H_0$ and $S_8$ tensions. Such small-scale clumping, which may be caused by primordial magnetic fields or baryon isocurvature below kpc scales, enhances the recombination rate even when averaged over larger scales, shifting recombination to earlier times. We introduce a flexible clumping model, parametrized via three spatial zones with free densities and volume fractions, and use it to study the impact of clumping on CMB observables. We find that increasing $H_0$ decreases both $\Omega_m$ and $S_8$, which alleviates the $S_8$ tension. On the other hand, the shift in $\Omega_m$ is disfavored by the low-$z$ baryon-acoustic-oscillations measurements. We find that the clumping parameters that can change the CMB sound horizon enough to explain the $H_0$ tension also alter the damping tail, so they are disfavored by current Planck 2018 data. We test how the CMB damping-tail information rules out changes to recombination by first removing $\ell>1000$ multipoles in Planck data, where we find that clumping could resolve the $H_0$ tension. Furthermore, we make predictions for future CMB experiments, as their improved damping-tail precision can better constrain departures from standard recombination. Both the Simons Observatory and CMB-S4 will provide decisive evidence for or against clumping as a resolution to the $H_0$ tension.

Cosmological constraints from the power spectrum of eBOSS emission line galaxies

We present cosmological parameter measurements from the effective field theory-based full-shape analysis of the power spectrum of emission line galaxies (ELGs). First, we perform extensive tests on simulations and determine appropriate scale cuts for the perturbative description of the ELG power spectrum. We study in detail non-linear redshift-space distortions (``fingers-of-God'') for this sample and show that they are somewhat weaker than those of luminous red galaxies. This difference is not significant for current data, but may become important for future surveys like Euclid/DESI. Then we analyze recent measurements of the ELG power spectrum from the extended Baryon acoustic Oscillation Spectroscopic Survey (eBOSS) within the $\nu\Lambda$CDM model. Combined with the BBN baryon density prior, the ELG pre- and post-reconstructed power spectra alone constrain the matter density $\Omega_m=0.257_{-0.045}^{+0.031}$, the current mass fluctuation amplitude $\sigma_8=0.571_{-0.076}^{+0.052}$, and the Hubble constant $H_0=84.5_{-7}^{+5.8}$ km/s/Mpc (all at 68\% CL). Combining with other full-shape and BAO data we measure $\Omega_m=0.327_{-0.016}^{+0.014}$, $\sigma_8=0.69_{-0.045}^{+0.038}$, and $H_0=68.6_{-1.1}^{+1}$ km/s/Mpc. The total neutrino mass is constrained to be $M_{\rm tot}<0.63$ eV (95\% CL) from the BBN, full-shape and BAO data only. Finally, we discuss the apparent $\sim 3\sigma$ discrepancy in the inferred clustering amplitude between our full shape analysis and the cosmic microwave background data.

Anisotropic effective redshift and evolving clustering amplitude

A typical galaxy survey geometry results in galaxy pairs of different separation and angle to the line-of-sight having different distributions in redshift and consequently a different effective redshift. However, clustering measurements are analysed assuming that the clustering is representative of that at a single effective redshift. We investigate the impact of variations in the galaxy-pair effective redshift on the large-scale clustering measured in galaxy surveys. We find that galaxy surveys spanning a large redshift range have different effective redshifts as a function of both pair separation and angle. Furthermore, when considering tracers whose clustering amplitude evolves strongly with redshift, this combination can result in an additional scale-dependent clustering anisotropy. We demonstrate the size of this effect on the eBOSS DR16 Quasar sample and show that, while the impact on monopole is negligible, neglecting this effect can result in a tilt of ∼ 4% and ∼40% in quadrupole and hexadecapole, respectively, on scales ∼1 h -1Gpc. We discuss strategies to mitigate this effect when making measurements.

A joint 2- and 3-point clustering analysis of the VIPERS PDR2 catalogue at z ∼ 1: breaking the degeneracy of cosmological parameters

ABSTRACT We measure the galaxy two- and three-point correlation functions at z = [0.5, 0.7] and z = [0.7, 0.9], from the Public Data Release 2 (PDR2) of the VIMOS Public Extragalactic Redshift Survey (VIPERS). We model the two statistics including a non-linear one-loop model for the two-point function and a tree-level model for the three-point function, and perform a joint likelihood analysis. The entire process and non-linear corrections are tested and validated through the use of the 153 highly realistic VIPERS mock catalogues, showing that they are robust down to scales as small as 10 $h^{-1} \, \mathrm{Mpc}$. The mocks are also adopted to compute the covariance matrix that we use for the joint two- and three-point analysis. Despite the limited statistics of the two (volume-limited) subsamples analysed, we demonstrate that such a combination successfully breaks the degeneracy existing at two-point level between clustering amplitude σ8, linear bias b1, and the linear growth rate of fluctuations f. For the latter, in particular, we measure $f(z=0.61)=0.64^{+0.55}_{-0.37}$ and f(z = 0.8) = 1.0 ± 1.0, while the amplitude of clustering is found to be σ8(z = 0.61) = 0.50 ± 0.12 and $\sigma _8(z=0.8)=0.39^{+0.11}_{-0.13}$. These values are in excellent agreement with the extrapolation of a Planck cosmology.

Euclid: Impact of non-linear and baryonic feedback prescriptions on cosmological parameter estimation from weak lensing cosmic shear

Upcoming surveys will map the growth of large-scale structure with unprecented precision, improving our understanding of the dark sector of the Universe. Unfortunately, much of the cosmological information is encoded on small scales, where the clustering of dark matter and the effects of astrophysical feedback processes are not fully understood. This can bias the estimates of cosmological parameters, which we study here for a joint analysis of mock Euclid cosmic shear and Planck cosmic microwave background data. We use different implementations for the modelling of the signal on small scales and find that they result in significantly different predictions. Moreover, the different non-linear corrections lead to biased parameter estimates, especially when the analysis is extended into the highly non-linear regime, with the Hubble constant, H0, and the clustering amplitude, σ8, affected the most. Improvements in the modelling of non-linear scales will therefore be needed if we are to resolve the current tension with more and better data. For a given prescription for the non-linear power spectrum, using different corrections for baryon physics does not significantly impact the precision of Euclid, but neglecting these correction does lead to large biases in the cosmological parameters. In order to extract precise and unbiased constraints on cosmological parameters from Euclid cosmic shear data, it is therefore essential to improve the accuracy of the recipes that account for non-linear structure formation, as well as the modelling of the impact of astrophysical processes that redistribute the baryons.

Organised randoms: Learning and correcting for systematic galaxy clustering patterns in KiDS using self-organising maps

We present a new method for the mitigation of observational systematic effects in angular galaxy clustering through the use of corrective random galaxy catalogues. Real and synthetic galaxy data from the Kilo Degree Survey’s (KiDS) 4th Data Release (KiDS-1000) and the Full-sky Lognormal Astro-fields Simulation Kit package, respectively, are used to train self-organising maps to learn the multivariate relationships between observed galaxy number density and up to six systematic-tracer variables, including seeing, Galactic dust extinction, and Galactic stellar density. We then create ‘organised’ randoms; random galaxy catalogues with spatially variable number densities, mimicking the learnt systematic density modes in the data. Using realistically biased mock data, we show that these organised randoms consistently subtract spurious density modes from the two-point angular correlation function w(ϑ), correcting biases of up to 12σ in the mean clustering amplitude to as low as 0.1σ, over an angular range of 7 − 100 arcmin with high signal-to-noise ratio. Their performance is also validated for angular clustering cross-correlations in a bright, flux-limited subset of KiDS-1000, comparing against an analogous sample constructed from highly complete spectroscopic redshift data. Each organised random catalogue object is a clone carrying the properties of a real galaxy, and is distributed throughout the survey footprint according to the position of the parent galaxy in systematics space. Thus, sub-sample randoms are readily derived from a single master random catalogue through the same selection as applied to the real galaxies. Our method is expected to improve in performance with increased survey area, galaxy number density, and systematic contamination, making organised randoms extremely promising for current and future clustering analyses of faint samples.

Deep21: a deep learning method for 21 cm foreground removal

We seek to remove foreground contaminants from 21 cm intensity mapping observations. We demonstrate that a deep convolutional neural network (CNN) with a UNet architecture and three-dimensional convolutions, trained on simulated observations, can effectively separate frequency and spatial patterns of the cosmic neutral hydrogen (HI) signal from foregrounds in the presence of noise. Cleaned maps recover cosmological clustering amplitude and phase within 20% at all relevant angular scales and frequencies. This amounts to a reduction in prediction variance of over an order of magnitude across angular scales, and improved accuracy for intermediate radial scales (0.025 < k∥ < 0.075 h Mpc-1) compared to standard Principal Component Analysis (PCA) methods. We estimate epistemic confidence intervals for the network's prediction by training an ensemble of UNets. Our approach demonstrates the feasibility of analyzing 21 cm intensity maps, as opposed to derived summary statistics, for upcoming radio experiments, as long as the simulated foreground model is sufficiently realistic.We provide the code used for this analysis on GitHub , as well as a browser-based tutorial for the experiment and UNet model via the accompanying Colab notebook .

The AGN–galaxy–halo connection: the distribution of AGN host halo masses to z = 2.5

ABSTRACT It is widely reported, based on clustering measurements of observed active galactic nucleus (AGN) samples, that AGNs reside in similar mass host dark matter haloes across the bulk of cosmic time, with log $\mathcal {M}/\mathcal {M}_{\odot }\sim 12.5\!-\!13.0$ to z ∼ 2.5. We show that this is due in part to the AGN fraction in galaxies rising with increasing stellar mass, combined with AGN observational selection effects that exacerbate this trend. Here, we use AGN specific accretion rate distribution functions determined as a function of stellar mass and redshift for star-forming and quiescent galaxies separately, combined with the latest galaxy–halo connection models, to determine the parent and subhalo mass distribution function of AGNs to various observational limits. We find that while the median (sub)halo mass of AGNs, $\approx 10^{12}\mathcal {M}_{\odot }$, is fairly constant with luminosity, specific accretion rate, and redshift, the full halo mass distribution function is broad, spanning several orders of magnitude. We show that widely used methods to infer a typical dark matter halo mass based on an observed AGN clustering amplitude can result in biased, systematically high host halo masses. While the AGN satellite fraction rises with increasing parent halo mass, we find that the central galaxy is often not an AGN. Our results elucidate the physical causes for the apparent uniformity of AGN host haloes across cosmic time and underscore the importance of accounting for AGN selection biases when interpreting observational AGN clustering results. We further show that AGN clustering is most easily interpreted in terms of the relative bias to galaxy samples, not from absolute bias measurements alone.

Blinded challenge for precision cosmology with large-scale structure: Results from effective field theory for the redshift-space galaxy power spectrum

An accurate theoretical template for the galaxy power spectrum is key for the success of ongoing and future spectroscopic surveys. We examine to what extent the effective field theory (EFT) of large-scale structure is able to provide such a template and correctly estimate cosmological parameters. To that end, we initiate a blinded challenge to infer cosmological parameters from the redshift-space power spectrum of high-resolution mock catalogs mimicking the BOSS galaxy sample but covering a 100 times larger cumulative volume. This gigantic simulation volume allows us to separate systematic bias due to theoretical modeling from the statistical error due to sample variance. The challenge is to measure three unknown input parameters used in the simulation: the Hubble constant, the matter density fraction, and the clustering amplitude. We present analyses done by two independent teams, who have fitted the mock simulation data generated by yet another independent group. This allows us to avoid any confirmation bias by analyzers and to pin down possible tuning of the specific EFT implementations. Both independent teams have recovered the true values of the input parameters within subpercent statistical errors corresponding to the total simulation volume.

The clustering of DESI-like luminous red galaxies using photometric redshifts

ABSTRACT We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging data set, and use the halo occupation distribution (HOD) framework to fit the clustering signal. The photometric LRG sample in this study contains 2.7 million objects over the redshift range of 0.4 &amp;lt; z &amp;lt; 0.9 over 5655 deg2. We have developed new photometric redshift (photo-z) estimates using the Legacy Survey DECam and WISE photometry, with σNMAD = 0.02 precision for LRGs. We compute the projected correlation function using new methods that maximize signal-to-noise ratio while incorporating redshift uncertainties. We present a novel algorithm for dividing irregular survey geometries into equal-area patches for jackknife resampling. For a five-parameter HOD model fit using the MultiDark halo catalogue, we find that there is little evolution in HOD parameters except at the highest redshifts. The inferred large-scale structure bias is largely consistent with constant clustering amplitude over time. In an appendix, we explore limitations of Markov chain Monte Carlo fitting using stochastic likelihood estimates resulting from applying HOD methods to N-body catalogues, and present a new technique for finding best-fitting parameters in this situation. Accompanying this paper, we have released the Photometric Redshifts for the Legacy Surveys catalogue of photo-z’s obtained by applying the methods used in this work to the full Legacy Survey Data Release 8 data set. This catalogue provides accurate photometric redshifts for objects with z &amp;lt; 21 over more than 16 000 deg2 of sky.

Forecasting cosmological constraints from the weak lensing magnification of type Ia supernovae measured by the Nancy Grace Roman Space Telescope

The weak lensing magnification of Type Ia Supernovae (SNe Ia) is sensitive to the clustering of matter, and provides an independent cosmological probe complementary to SN Ia distance measurements. The Nancy Grace Roman Space Telescope is uniquely sensitive to this measurement as it can discover high redshift SNe Ia and measure them with high precision. We present a methodology for reconstructing the probability distribution of the weak lensing magnification $\mu$ of SNe Ia, $p(\mu)$, from observational data, and using it to constrain cosmological parameters. We find that the reconstructed $p(\mu)$ can be fitted accurately by a stretched Gaussian distribution, and used to measure the variance of $\mu$, $\xi_\mu$, which can be compared to theoretical predictions in a likelihood analysis. Applying our methodology to a set of realistically simulated SNe Ia expected from the Roman Space Telescope, we find that using the weak lensing magnification of the SNe Ia constrains a combination of matter density $\Omega_m$ and matter clustering amplitude $\sigma_8$. SN Ia distances alone lead to a better than 1\% measurement of $\Omega_m$. The combination of SN Ia weak lensing magnification and distance measurements result in a $\sim$ 10\% measurement on $\sigma_8$. The SNe Ia from Roman will be powerful in constraining the cosmological model.