Galaxy Density Field Research Articles

The gravitational lensing imprints of DES Y3 superstructures on the CMB: a matched filtering approach

ABSTRACT Low-density cosmic voids gravitationally lens the cosmic microwave background (CMB), leaving a negative imprint on the CMB convergence $\kappa$. This effect provides insight into the distribution of matter within voids, and can also be used to study the growth of structure. We measure this lensing imprint by cross-correlating the Planck CMB lensing convergence map with voids identified in the Dark Energy Survey Year 3 (DES Y3) data set, covering approximately 4200 deg$^2$ of the sky. We use two distinct void-finding algorithms: a 2D void-finder that operates on the projected galaxy density field in thin redshift shells, and a new code, Voxel, which operates on the full 3D map of galaxy positions. We employ an optimal matched filtering method for cross-correlation, using the Marenostrum Institut de Ciències de l’Espai N-body simulation both to establish the template for the matched filter and to calibrate detection significances. Using the DES Y3 photometric luminous red galaxy sample, we measure $A_\kappa$, the amplitude of the observed lensing signal relative to the simulation template, obtaining $A_\kappa = 1.03 \pm 0.22$ ($4.6\sigma$ significance) for Voxel and $A_\kappa = 1.02 \pm 0.17$ ($5.9\sigma$ significance) for 2D voids, both consistent with Lambda cold dark matter expectations. We additionally invert the 2D void-finding process to identify superclusters in the projected density field, for which we measure $A_\kappa = 0.87 \pm 0.15$ ($5.9\sigma$ significance). The leading source of noise in our measurements is Planck noise, implying that data from the Atacama Cosmology Telescope, South Pole Telescope and CMB-S4 will increase sensitivity and allow for more precise measurements.

Large-scale Structures in COSMOS2020: Evolution of Star Formation Activity in Different Environments at 0.4 < z < 4

To study the role of environment in galaxy evolution, we reconstruct the underlying density field of galaxies based on COSMOS2020 (The Farmer catalog) and provide the density catalog for a magnitude-limited (K s < 24.5) sample of ∼210,000 galaxies at 0.4 < z < 5 within the COSMOS field. The environmental densities are calculated using a weighted kernel density estimation approach with the choice of a von Mises–Fisher kernel, an analog of the Gaussian kernel for periodic data. Additionally, we make corrections for the edge effect and masked regions in the field. We utilize physical properties extracted by LePhare to investigate the connection between star formation activity and the environmental density of galaxies in six mass-complete subsamples at different cosmic epochs within 0.4 < z < 4. Our findings confirm a strong anticorrelation between star formation rate (SFR)/specific SFR (sSFR) and environmental density out to z ∼ 1.1. At 1.1 < z < 2, there is no significant correlation between SFR/sSFR and density. At 2 < z < 4, we observe a reversal of the SFR/sSFR–density relation such that both SFR and sSFR increase by a factor of ∼10 with increasing density contrast, δ, from −0.4 to 5. This observed reversal at higher redshifts supports the scenario where an increased availability of gas supply, along with tidal interactions and a generally higher star formation efficiency in dense environments, could potentially enhance star formation activity in galaxies located in rich environments at z > 2.

Cosmological parameters estimated from peculiar velocity–density comparisons: calibrating 2M++

ABSTRACT Cosmological parameters can be measured by comparing peculiar velocities with those predicted from a galaxy density field. Previous work has tested the accuracy of this approach with N-body simulations, but generally on idealized mock galaxy surveys. However, systematic biases may arise solely due to survey selection effects such as flux-limited samples, edge-effects, and complications due to the obscuration of the Galactic plane. In this work, we explore the impact of each of these effects individually as well as collectively using the semi-analytic models from numerical simulations to generate mock catalogues that mimic the 2M++ density field. We find the reconstruction and analysis methods used for our 2M++ mocks produce a value of fσ8 that is biased high by a factor 1.04 ± 0.01 compared to the true value. Moreover, a cosmic volume matching that of 2M++ has a cosmic variance uncertainty in fσ8 of $\sim 5~{{\ \rm per\ cent}}$. The systematic bias is a function of distance: it is unbiased close to the origin but is biased slightly high for distances in the range 100–180 h−1 Mpc. Correcting for this small bias, we find that recent peculiar velocity samples yield $f\sigma _8^{\textrm {lin}} = 0.362\pm 0.023$, a value that is in tension with the extrapolations from cosmic microwave background measurements. The predicted peculiar velocities from 2M++ have an error of 170 km s−1 that slowly increases with distance, exceeding 200 km s−1 only at distances of 180–200 h−1Mpc. Finally, the residual bulk flow speeds found in previous work are shown to be not in conflict with those expected in the Λ cold dark matter model.

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.

Cluster-counterpart Voids: Void Identification from Galaxy Density Field

We identify cosmic voids from galaxy density fields under the theory of void–cluster correspondence. We extend the previous novel void-identification method developed for the matter density field to the galaxy density field for practical applications. From cosmological N-body simulations, we construct galaxy number- and mass-weighted density fields to identify cosmic voids that are counterparts of galaxy clusters of a specific mass. The parameters for the cluster-counterpart void identification such as Gaussian smoothing scale, density threshold, and core volume fraction are found for galaxy density fields. We achieve about 60%–67% of completeness and reliability for identifying the voids of corresponding cluster mass above 3 × 1014 h −1 M ⊙ from a galaxy sample with the mean number density, . When the mean density is increased to , the detection rate is enhanced by ∼2%–7% depending on the mass scale of voids. We find that the detectability is insensitive to the density weighting scheme applied to generate the density field. Our result demonstrates that we can apply this method to the galaxy redshift survey data to identify cosmic voids corresponding statistically to the galaxy clusters in a given mass range.

Spurious Correlations between Galaxies and Multiepoch Image Stacks in the DESI Legacy Surveys

A nonnegligible source of systematic bias in cosmological analyses of galaxy surveys is the on-sky modulation that is caused by foregrounds and variable image characteristics, such as observing conditions. Standard mitigation techniques perform a regression between the observed galaxy density field and sky maps of the potential contaminants. Such maps are ad hoc lossy summaries of the heterogeneous sets of coadded exposures that contribute to the survey. We present a methodology for addressing this limitation, and we extract spurious correlations between the observed distributions of galaxies and arbitrary stacks of single-epoch exposures. We study four types of galaxies (luminous red galaxies, emission-line galaxies, quasars, and Lyman-break galaxies) in the three regions of the DESI Legacy Surveys (North, South, and Dark Energy Survey), resulting in 12 samples with varying levels and types of contamination. We find that the new technique outperforms the traditional ones in all cases, and is able to remove higher levels of contamination. This paves the way for new methods that extract more information from multiepoch galaxy survey data and mitigate large-scale biases more effectively.

Death at watersheds: Galaxy quenching in low-density environments

Context.The evolution of galaxies is influenced by their local and global environment in the cosmic web. Galaxies with very old stellar populations (VO galaxies withDn(4000) index ≥1.75) mostly lie in the centres of galaxy clusters, where they evolve under the influence of processes characteristic of high-density cluster environments. However, VO galaxies have also been found in poor groups in global low-density environments between superclusters, which we call watershed regions.Aims.Our aim is to analyse the properties of galaxies in various cosmic environments with a focus on VO galaxies in the watershed regions to understand their evolution, and the origin of the large-scale morphology–density relation.Methods.We employ the Sloan Digital Sky Survey DR10 MAIN spectroscopic galaxy sample in the redshift range 0.009 ≤ z ≤ 0.200 to calculate the luminosity–density field of galaxies, to determine groups and filaments in the galaxy distribution, and to obtain data on galaxy properties. The luminosity–density field with smoothing length 8h−1Mpc,D8, characterises the global environment of galaxies. We analyse the group and galaxy contents of regions with variousD8 thresholds. We divide groups into low- and high-luminosity groups based on the highest luminosity of groups in the watershed region,Lgr ≤ 15 × 1012h−2L⊙. We compare the stellar masses, the concentration index, and the stellar velocity dispersions of quenched and star-forming galaxies among single galaxies, satellite galaxies, and the brightest group galaxies (BGGs) in various environments.Results.We show that the global density is most strongly related to the richness of galaxy groups. Its influence on the overall star formation quenching in galaxies is less strong. Correlations between the morphological properties of galaxies and the global density field are the weakest. The watershed regions withD8 &lt; 1 are populated mostly by single galaxies, constituting 70% of all galaxies there, and by low-luminosity groups. Still, approximately one-third of all galaxies in the watershed regions are VO galaxies. They have lower stellar masses, smaller stellar velocity dispersions, and stellar populations that are up to 2 Gyr younger than those of VO galaxies in other global environments. In higher density global environments (D8 &gt; 1), the morphological properties of galaxies are very similar. Differences in galaxy properties are the largest between satellites and BGGs in groups.Conclusions.Our results suggest that galaxy evolution is determined by the birthplace of galaxies in the cosmic web, and mainly by internal processes which lead to the present-day properties of galaxies. This may explain the similarity of (VO) galaxies in extremely different environments.

Primordial trispectrum from kinetic Sunyaev-Zel’dovich tomography

The kinetic Sunyaev Zel'dovich effect is a secondary CMB temperature anisotropy that provides a powerful probe of the radial-velocity field of matter distributed across the Universe. This velocity field is reconstructed by combining high-resolution CMB measurements with galaxy survey data, and it provides an unbiased tracer of matter perturbations in the linear regime. In this paper, we show how this measurement can be used to probe primordial non-Gaussianity of the local type, particularly focusing on the trispectrum amplitude $\tau_{\rm NL}$, as may arise in a simple two-field inflation model that we provide by way of illustration. Cross-correlating the velocity-field-derived matter distribution with the biased large-scale galaxy density field allows one to measure the scale-dependent bias factor with sample variance cancellation. We forecast that a configuration corresponding to CMB-S4 and VRO results in a sensitivity of $\sigma_{f_{\rm NL}} \approx 0.59$ and $\sigma_{\tau_{\rm NL}} \approx 1.5$. These forecasts predict improvement factors of 10 and 195 for $\sigma_{f_{\rm NL}}$ and $\sigma_{\tau_{\rm NL}}$, respectively, over the sensitivity using VRO data alone, without internal sample variance cancellation. Similarly, for a configuration corresponding to DESI and SO, we forecast a sensitivity of $\sigma_{f_{\rm NL}} \approx 3.1$ and $\sigma_{\tau_{\rm NL}} \approx 69$, with improvement factors of 2 and 5, respectively, over the use of the DESI data-set in isolation. We find that a high galaxy number density and large survey volume considerably improve our ability to probe the amplitude of the primordial trispectrum for the multi-field model considered.

Tightening geometric and dynamical constraints on dark energy and gravity: Galaxy clustering, intrinsic alignment, and kinetic Sunyaev-Zel’dovich effect

Conventionally, in galaxy surveys, cosmological constraints on the growth and expansion history of the Universe have been obtained from the measurements of redshift-space distortions and baryon acoustic oscillations embedded in the large-scale galaxy density field. In this paper, we study how well one can improve the cosmological constraints from the combination of the galaxy density field with velocity and tidal fields, which are observed via the kinetic Sunyaev-Zel'dovich (kSZ) and galaxy intrinsic alignment (IA) effects, respectively. For illustration, we consider the deep galaxy survey by Subaru Prime Focus Spectrograph, whose survey footprint perfectly overlaps with the imaging survey of the Hyper Suprime-Cam and the CMB-S4 experiment. We find that adding the kSZ and IA effects significantly improves cosmological constraints, particularly when we adopt the nonflat cold dark matter model which allows both time variation of the dark energy equation-of-state and deviation of the gravity law from general relativity. Under this model, we achieve 31% improvement for the growth index $\ensuremath{\gamma}$ and $&gt;35%$ improvement for other parameters except for the curvature parameter, compared to the case of the conventional galaxy-clustering-only analysis. As another example, we also consider the wide Galaxy survey by the Euclid satellite, in which shapes of galaxies are noisier but the survey volume is much larger. We demonstrate that when the above model is adopted, the clustering analysis combined with kSZ and IA from the deep survey can achieve tighter cosmological constraints than the clustering-only analysis from the wide survey.

Cross Correlation between the Thermal Sunyaev–Zel’dovich Effect and Projected Galaxy Density Field

We present a joint analysis of the power spectra of the Planck Compton y parameter map and the projected galaxy density field using the Wide Field Infrared Survey Explorer (WISE) all-sky survey. We detect the statistical correlation between WISE and Planck data (gy) with a significance of 21.8σ. We also measure the autocorrelation spectrum for the thermal Sunyaev–Zel’dovich (tSZ) (yy) and the galaxy density field maps (gg) with a significance of 150σ and 88σ, respectively. We then construct a halo model and use the measured correlations , , and to constrain the tSZ mass bias . We also fit for the galaxy bias, which is included with explicit redshift and multipole dependencies as , with ℓ 0 = 117. We obtain the constraints to be B = 1.50 ± 0.07(stat) ± 0.34(sys), i.e., 1 − b H = 0.67 ± 0.03(stat) ± 0.16(sys) (68% confidence level) for the hydrostatic mass bias, and , with and β = 0.45 ±0.01(stat) ± 0.02(sys) for the galaxy bias. Incoming data sets from future CMB and galaxy surveys (e.g., Rubin Observatory) will allow probing the large-scale gas distribution in more detail.

Impact of thermal Sunyaev–Zeldovich effect on cross-correlations between Planck cosmic microwave background lensing and SDSS galaxy density fields

ABSTRACT Residual foreground contamination by thermal Sunyaev–Zeldovich (tSZ) effect from galaxy clusters in cosmic microwave background (CMB) maps propagates into the reconstructed CMB lensing field, and thus biases the intrinsic cross-correlation between CMB lensing and large-scale structure (LSS). Through stacking analysis, we show that residual tSZ contamination causes an increment of lensing convergence in the central part of the clusters and a decrement of lensing convergence in the cluster outskirts. We quantify the impact of residual tSZ contamination on cross-correlations between the Planck 2018 CMB lensing convergence maps and the Sloan Digital Sky Survey-IV galaxy density data through cross-power spectrum computation. In contrast with the Planck 2018 tSZ-deprojected smica lensing map, our analysis using the tSZ-contaminated smica lensing map measures an $\sim\!2.5{{\ \rm per\,cent}}$ negative bias at multipoles ℓ ≲ 500 and transits to an $\sim\!9{{\ \rm per\,cent}}$ positive bias at ℓ ≳ 1500, which validates earlier theoretical predictions of the overall shape of such tSZ-induced spurious cross-correlation. The tSZ-induced lensing convergence field in Planck CMB data is detected with more than 1σ significance at ℓ ≲ 500 and more than 14σ significance at ℓ ≳ 1500, yielding an overall 14.8σ detection. We also show that masking galaxy clusters in CMB data is not sufficient to eliminate the spurious lensing signal, still detecting a non-negligible bias with 5.5σ significance on cross-correlations with galaxy density fields. Our results emphasize how essential it is to deproject the tSZ effect from CMB maps at the component separation stage and adopt tSZ-free CMB lensing maps for cross-correlations with LSS data.

Cosmology behind the mask: Constraining the parameters of ΛCDM with the unmasked galaxy density field from VIPERS

Abstract Galaxy redshift surveys are designed to map cosmic structures in three dimensions for large-scale structure studies. Nevertheless, limitations due to sampling and the survey window are unavoidable and degrade the cosmological constraints. We present an analysis of the VIMOS Public Extragalactic Redshift Survey (VIPERS) over the redshift range 0.6 &amp;lt; z &amp;lt; 1 that is optimised to extract the cosmological parameters while fully accounting for the complex survey geometry. We employ the Gibbs sampling algorithm to iteratively draw samples of the galaxy density field in redshift space, the galaxy bias, the matter density, baryon fraction and growth-rate parameter fσ8 based on a multivariate Gaussian likelihood and prior on the density field. Despite the high number of degrees of freedom, the samples converge to the joint posterior distribution and give self-consistent constraints on the model parameters. We validate the approach using VIPERS mock galaxy catalogues. Although the uncertainty is underestimated by the Gaussian likelihood on the scales that we consider by 50%, the dispersion of the results from the mock catalogues gives a robust error estimate. We find that the precision of the results matches those of the traditional analyses applied to the VIPERS data that use more constrained models. By relaxing the model assumptions, we confirm that the data deliver consistent constraints on the ΛCDM model. This work provides a case-study for the application of maximum-likelihood analyses for the next generation of galaxy redshift surveys.

Bent It Like FRs: Extended Radio AGN in the COSMOS Field and Their Large-Scale Environment

A fascinating topic in radio astronomy is how to associate the complexity of observed radio structures with their environment in order to understand their interplay and the reason for the plethora of radio structures found in surveys. In this project, we explore the distortion of the radio structure of Fanaroff–Riley (FR)-type radio sources in the VLA-COSMOS Large Project at 3 GHz and relate it to their large-scale environment. We quantify the distortion by using the angle formed between the jets/lobes of two-sided FRs, namely bent angle (BA). Our sample includes 108 objects in the redshift range 0.08&lt;z&lt;3, which we cross-correlate to a wide range of large-scale environments (X-ray galaxy groups, density fields, and cosmic web probes) in the COSMOS field. The median BA of FRs in COSMOS at zmed∼0.9 is 167.5−37.5+11.5 degrees. We do not find significant correlations between BA and large-scale environments within COSMOS covering scales from a few kpc to several hundred Mpc, nor between BA and host properties. Finally, we compare our observational data to magnetohydrodynamical (MHD) adaptive-mesh simulations ENZO-MHD of two FR sources at z = 0.5 and at z = 1. Although the scatter in BA of the observed data is large, we see an agreement between observations and simulations in the bent angles of FRs, following a mild redshift evolution with BA. We conclude that, for a given object, the dominant mechanism affecting the radio structures of FRs could be the evolution of the ambient medium, where higher densities of the intergalactic medium at lower redshifts as probed by our study allow more space for jet interactions.

Lagrangian approach to super-sample effects on biased tracers at field level: galaxy density fields and intrinsic alignments

It has been recognized that the observables of large-scale structure (LSS) is susceptible to long-wavelength density and tidal fluctuations whose wavelengths exceed the accessible scale of a finite-volume observation, referred to as the super-sample modes. The super-sample modes modulate the growth and expansion rate of local structures, thus affecting the cosmological information encoded in the statistics of galaxy clustering data. In this paper, based on the Lagrangian perturbation theory, we develop a new formalism to systematically compute the response of a biased tracer of LSS, which is expressed perturbatively in terms of the matter density field of sub-survey modes, to the super-sample modes at the field level. The formalism presented here reproduces the power spectrum responses that have been previously derived, and provides an alternative way to compute statistical quantities with super-sample modes. As an application, we consider the statistics of the intrinsic alignments of galaxies and halos, and derive the field response of the galaxy/halo shape bias to the super-sample modes. Possible impacts of the long-mode contributions on the covariance of the three-dimensional power spectra of the intrinsic alignment are also discussed, and the signal-to-noise ratios are estimated.

The large-scale monopole of the power spectrum in a Euclid-like survey: wide-angle effects, lensing, and the ‘finger of the observer’

ABSTRACT Radial redshift-space distortions due to peculiar velocities and other light-cone effects shape the maps we build of the Universe. We address the open question of their impact onto the monopole moment of the galaxy power spectrum, P0(k). Specifically, we use an upgraded numerical implementation of the liger method to generate 140 mock galaxy density fields for a full Euclid-like survey and we measure P0(k) in each of them utilizing a standard estimator. We compare the spectra obtained by turning on and off different effects. Our results show that wide-angle effects due to radial peculiar velocities generate excess power above the level expected within the plane–parallel approximation. They are detectable with a signal-to-noise ratio of 2.7 for $k\lt 0.02\, h$ Mpc−1. Weak-lensing magnification also produces additional power on large scales which, if the current favourite model for the luminosity function of Hα emitters turns out to be realistic, can only be detected with a signal-to-noise ratio of 1.3 at best. Finally, we demonstrate that measuring P0(k) in the standard of rest of the observer generates an additive component reflecting the kinematic dipole overdensity caused by the peculiar velocity. This component is characterized by a damped oscillatory pattern on large scales. We show that this ‘finger of the observer’ effect is detectable in some redshift bins and suggest that its measurement could possibly open new research directions in connection with the determination of the cosmological parameters, the properties of the galaxy population under study, and the dipole itself.

Biasing Phenomenon

We study biasing as a physical phenomenon by analysing power spectra (PS) and correlation functions (CF) of simulated galaxy samples and dark matter (DM) samples. We apply an algorithm based on the local densities of particles, $\rho$, to form populations of simulated galaxies, using particles with $\rho \ge \rho_0$. We calculate two-point CF of projected (2D) and spatial (3D) density fields of simulated galaxies for various particle-density limits $\rho_0$. We compare 3D and 2D CFs; in 2D case we use samples of various thickness to find the dependence of 2D CFs on thickness of samples. Dominant elements of the cosmic web are clusters and filaments, separated by voids filling most of the volume. In individual 2D sheets positions of clusters and filaments do not coincide. As a result, in projection clusters and filaments fill in 2D voids. This leads to the decrease of amplitudes of CFs in projection. For this reason amplitudes of 2D CFs are lower than amplitudes of 3D CFs, the difference is the larger, the thicker are 2D samples. Using PS and CFs of simulated galaxies and DM we estimate the bias factor for $L^\ast$ galaxies, $b^\ast =1.85 \pm 0.15$.

Correlation functions in 2D and 3D as descriptors of the cosmic web

Aims. Our goal is to find the relation between the two-point correlation functions (CFs) of projected and spatial density fields of galaxies in the context of the cosmic web. Methods. To investigate relations between spatial (3D) and projected (2D) CFs of galaxies we used density fields of two simulations: a Λ-dominated cold dark matter model with known particle data, and the Millennium simulation with know data on simulated galaxies. We compare 3D and 2D correlation functions. In the 2D case, we use samples of various thickness to find the dependence of 2D CFs on the thickness of samples. We also compare 3D CFs in real and redshift space. Results. The dominant elements of the cosmic web are clusters and filaments, separated by voids filling most of the volume. In individual 2D sheets, the positions of clusters and filaments do not coincide. As a result, in projection, the clusters and filaments fill in 2D voids. This leads to a decrease in the amplitudes of CFs (and power spectra) in projection. For this reason, the amplitudes of 2D CFs are lower than the amplitudes of 3D correlation functions: the thicker the 2D sample, the greater the difference. Conclusions. Spatial CFs of galaxies contain valuable information about the geometrical properties of the cosmic web that cannot be found from projected CFs.

Redshift-space distortions with split densities

ABSTRACT Accurate modelling of redshift-space distortions (RSD) is challenging in the non-linear regime for two-point statistics e.g. the two-point correlation function (2PCF). We take a different perspective to split the galaxy density field according to the local density, and cross-correlate those densities with the entire galaxy field. Using mock galaxies, we demonstrate that combining a series of cross-correlation functions (CCFs) offers improvements over the 2PCF as follows: (1) The distribution of peculiar velocities in each split density is nearly Gaussian. This allows the Gaussian streaming model for RSD to perform accurately within the statistical errors of a ($1.5\, h^{-1}$ Gpc)3 volume for almost all scales and all split densities. (2) The probability distribution of the density contrast at small scales is non-Gaussian, but the CCFs of split densities capture the non-Gaussianity, leading to improved cosmological constraints over the 2PCF. We can obtain unbiased constraints on the growth parameter fσ12 at the per cent level, and Alcock–Paczynski (AP) parameters at the sub-per cent level with the minimal scale of $15\, h^{-1}{\rm Mpc}$. This is a ∼30 per cent and ∼6 times improvement over the 2PCF, respectively. The diverse and steep slopes of the CCFs at small scales are likely to be responsible for the improved constraints of AP parameters. (3) Baryon acoustic oscillations (BAO) are contained in all CCFs of split densities. Including BAO scales helps to break the degeneracy between the line-of-sight and transverse AP parameters, allowing independent constraints on them. We discuss and compare models for RSD around spherical densities.

Linear systematics mitigation in galaxy clustering in the Dark Energy Survey Year 1 Data

ABSTRACT We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment (1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself, (2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints, (3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field, and (4) is fully automated, and can therefore be trivially applied to any data set. The updated correlation function for the DES Y1 redMaGiC catalogue minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness-of-fit statistic of the DES Y1 3 × 2pt data set (Δχ2 = −6.5 with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.