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In the near future, the overlap of the Rubin Observatory Legacy Survey of Space and Time (LSST) and the Simons Observatory (SO) will present an ideal opportunity for joint cosmological data set analyses. In this paper, we simulate the joint likelihood analysis of these two experiments using six two-point functions derived from galaxy position, galaxy shear, and CMB lensing convergence fields. Our analysis focuses on realistic noise and systematics models and we find that the dark energy Figure of merit (FoM) increases by 53 per cent (92 per cent) from LSST-only to LSST+SO in Year 1 (Year 6). We also investigate the benefits of using the same galaxy sample for both clustering and lensing analyses, and find the choice improves the overall signal to noise by ∼30−40 per cent, which significantly improves the photo-z calibration and mildly improves the cosmological constraints. Finally, we explore the effects of catastrophic photo-z outliers finding that they cause significant parameter biases when ignored. We develop a new mitigation approach termed ‘island model’, which corrects a large fraction of the biases with only a few parameters while preserving the constraining power.

The overlap of galaxy surveys and cosmic microwave background (CMB) experiments presents an ideal opportunity for joint cosmological data set analyses. In this paper we develop a halo model-based method for the first joint analysis combining these two experiments using 10 correlated two-point functions (10 × 2pt) derived from galaxy position, galaxy shear, CMB lensing convergence, and Compton- y fields. We explore this method using the Vera Rubin Observatory Legacy Survey of Space and Time (LSST) and the Simons Observatory (SO) as examples. We find such LSS × CMB joint analyses lead to significant improvement in Figure-of-Merit of Ωm and S 8 over the constraints from using LSS-only probes within Λ cold dark matter (ΛCDM) model. We identify that the shear– y and y–y correlations are the most valuable additions when thermal Sunyaev–Zel'dolvich (tSZ) is included. We further identify the dominant sources of halo model uncertainties in the small-scale modelling, and investigate the impact of halo self-calibration due to the inclusion of small-scale tSZ information. [ABSTRACT FROM AUTHOR]

We extend the modal decomposition method, previously applied to compress the information in the real-space bispectrum to the anisotropic redshift-space galaxy bispectrum. In the modal method approach, the bispectrum is expanded on a basis of smooth functions of triangles and their orientations, such that a set of modal expansion coefficients can capture the information in the bispectrum. We assume a reference survey and compute Fisher forecasts for the compressed modal bispectrum and two other basis decompositions of the redshift-space bispectrum in the literature, one based on (single) spherical harmonics and another based on tripolar spherical harmonics. In each case, we compare the forecasted constraints from the compressed statistic with forecasted constraints from the full uncompressed bispectrum which includes all triangles and orientations. Our main result is that all three compression methods achieve good recovery of the full information content of the bispectrum, but the modal decomposition approach achieves this the most efficiently: only 14 (42) modal expansion coefficients are necessary to obtain constraints that are within 10 (2) per cent of the full bispectrum result. The next most efficient decomposition is the one based on tripolar spherical harmonics, while the spherical harmonic multipoles are the least efficient. [ABSTRACT FROM AUTHOR]

We simulate the scientific performance of the Nancy Grace Roman Space Telescope High Latitude Survey (HLS) on dark energy and modified gravity. The 1.6-yr HLS Reference survey is currently envisioned to image 2000 deg2 in multiple bands to a depth of ∼26.5 in Y ,  J ,  H and to cover the same area with slit-less spectroscopy beyond z  = 3. The combination of deep, multiband photometry and deep spectroscopy will allow scientists to measure the growth and geometry of the Universe through a variety of cosmological probes (e.g. weak lensing, galaxy clusters, galaxy clustering, BAO, Type Ia supernova) and, equally, it will allow an exquisite control of observational and astrophysical systematic effects. In this paper, we explore multiprobe strategies that can be implemented, given the telescope's instrument capabilities. We model cosmological probes individually and jointly and account for correlated systematics and statistical uncertainties due to the higher order moments of the density field. We explore different levels of observational systematics for the HLS survey (photo -z and shear calibration) and ultimately run a joint likelihood analysis in N- dim parameter space. We find that the HLS reference survey alone can achieve a standard dark energy FoM of >300 when including all probes. This assumes no information from external data sets, we assume a flat universe however, and includes realistic assumptions for systematics. Our study of the HLS reference survey should be seen as part of a future community-driven effort to simulate and optimize the science return of the Roman Space Telescope. [ABSTRACT FROM AUTHOR]

Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3 × 2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modelling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude (Q 1) generally reflects the strength of baryon feedback. With the upper limit of Q 1 prior being bound by the Illustris feedback scenarios, we reach |$\sim 20{{\ \rm per\ cent}}$| improvement in the constraint of |$S_8=\sigma _8(\Omega _{\rm m}/0.3)^{0.5}=0.788^{+0.018}_{-0.021}$| compared to the original DES 3 × 2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 arcmin, which was excluded in previous DES analyses that did not model baryonic physics. We obtain |$S_8=0.781^{+0.014}_{-0.015}$| for the combined DES Y1+Planck EE+BAO analysis with a non-informative Q 1 prior. In terms of the baryon constraints, we measure |$Q_1=1.14^{+2.20}_{-2.80}$| for DES Y1 only and |$Q_1=1.42^{+1.63}_{-1.48}$| for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than 2σ. [ABSTRACT FROM AUTHOR]

We present a method of combining cluster abundances and large-scale two-point correlations, namely galaxy clustering, galaxy–cluster cross-correlations, cluster autocorrelations, and cluster lensing. This data vector yields comparable cosmological constraints to traditional analyses that rely on small-scale cluster lensing for mass calibration. We use cosmological survey simulations designed to resemble the Dark Energy Survey Year 1 (DES-Y1) data to validate the analytical covariance matrix and the parameter inferences. The posterior distribution from the analysis of simulations is statistically consistent with the absence of systematic biases detectable at the precision of the DES-Y1 experiment. We compare the χ2 values in simulations to their expectation and find no significant difference. The robustness of our results against a variety of systematic effects is verified using a simulated likelihood analysis of DES-Y1-like data vectors. This work presents the first-ever end-to-end validation of a cluster abundance cosmological analysis on galaxy catalogue level simulations. [ABSTRACT FROM AUTHOR]

Accurate covariance matrices for two-point functions are critical for inferring cosmological parameters in likelihood analyses of large-scale structure surveys. Among various approaches to obtaining the covariance, analytic computation is much faster and less noisy than estimation from data or simulations. However, the transform of covariances from Fourier space to real space involves integrals with two Bessel integrals, which are numerically slow and easily affected by numerical uncertainties. Inaccurate covariances may lead to significant errors in the inference of the cosmological parameters. In this paper, we introduce a 2D-FFTLog algorithm for efficient, accurate, and numerically stable computation of non-Gaussian real-space covariances for both 3D and projected statistics. The 2D-FFTLog algorithm is easily extended to perform real-space bin-averaging. We apply the algorithm to the covariances for galaxy clustering and weak lensing for a Dark Energy Survey Year 3-like and a Rubin Observatory's Legacy Survey of Space and Time Year 1-like survey, and demonstrate that for both surveys, our algorithm can produce numerically stable angular bin-averaged covariances with the flat sky approximation, which are sufficiently accurate for inferring cosmological parameters. The code CosmoCov for computing the real-space covariances with or without the flat-sky approximation is released along with this paper. [ABSTRACT FROM AUTHOR]

We explore strategies to extract cosmological constraints from a joint analysis of cosmic shear, galaxy-galaxy lensing, galaxy clustering, cluster number counts and cluster weak lensing. We utilize the COSMOLIKE software to simulate results from a Large Synoptic Survey Telescope (LSST) like data set, specifically, we (1) compare individual and joint analyses of the different probes, (2) vary the selection criteria for lens and source galaxies, (3) investigate the impact of blending, (4) investigate the impact of the assumed cosmological model in multiprobe covariances, (6) quantify information content as a function of scales and (7) explore the impact of intrinsic galaxy alignment in a multiprobe context. Our analyses account for all cross-correlations within and across probes and include the higher-order (non-Gaussian) terms in the multiprobe covariance matrix. We simultaneously model cosmological parameters and a variety of systematics, e.g. uncertainties arising from shear and photo-z calibration, cluster mass-observable relation, galaxy intrinsic alignment and galaxy bias (up to 54 parameters altogether). We highlight two results: first, increasing the number density of source galaxies by ~30 per cent, which corresponds to solving blending for LSST, only gains little information. Secondly, including small scales in clustering and galaxy-galaxy lensing, by utilizing halo occupation distribution models, can substantially boost cosmological constraining power. [ABSTRACT FROM AUTHOR]

Intrinsic alignment (IA) of source galaxies is one of the major astrophysical systematics for weak lensing surveys. Several IA models have been proposed and their impact on cosmological constraints has been examined using the Fisher information matrix in conjunction with approximate, Gaussian covariances. This paper presents the first forecasts of the impact of IA on cosmic shear measurements for future surveys using simulated likelihood analyses and covariances that include higher order moments of the density field. We consider a range of possible IA scenarios and test mitigation schemes which parametrize IA by the fraction of red galaxies, normalization, luminosity and redshift dependence of the IA signal. Compared to previous studies, we find smaller biases in time-dependent dark energy models if IA is ignored in the analysis. The amplitude and significance of these biases vary as a function of survey properties (depth, statistical uncertainties), luminosity function and IA scenario. Due to its small statistical errors and relatively shallow depth, Euclid is significantly impacted by IA. Large Synoptic Survey Telescope (LSST) andWide-Field Infrared Survey Telescope (WFIRST) benefit from increased survey depth, while larger statistical errors for Dark Energy Survey (DES) decrease IA's relative impact on cosmological parameters. The proposed IA mitigation scheme removes parameter biases for DES, LSST and WFIRST even if the shape of the IA power spectrum is only poorly known; successful IA mitigation for Euclid requires more prior information. We explore several alternative IA mitigation strategies for Euclid; in the absence of alignment of blue galaxies we recommend the exclusion of red (IA-contaminated) galaxies in cosmic shear analyses. [ABSTRACT FROM AUTHOR]

Systematic uncertainties that have been subdominant in past large-scale structure (LSS) surveys are likely to exceed statistical uncertainties of current and future LSS data sets, potentially limiting the extraction of cosmological information. Here we present a general framework (Principal Component Analysis - PCA - marginalization) to consistently incorporate systematic effects into a likelihood analysis. This technique naturally accounts for degeneracies between nuisance parameters and can substantially reduce the dimension of the parameter space that needs to be sampled. As a practical application, we apply PCA marginalization to account for baryonic physics as an uncertainty in cosmic shear tomography. Specifically, we use COSMOLIKE to run simulated likelihood analyses on three independent sets of numerical simulations, each covering a wide range of baryonic scenarios differing in cooling, star formation, and feedback mechanisms. We simulate a Stage III (Dark Energy Survey) and Stage IV (Large Synoptic Survey Telescope/Euclid) survey and find a substantial bias in cosmological constraints if baryonic physics is not accounted for. We then show that PCA marginalization (employing at most three to four nuisance parameters) removes this bias. Our study demonstrates that it is possible to obtain robust, precise constraints on the dark energy equation of state even in the presence of large levels of systematic uncertainty in astrophysical processes. We conclude that the PCA marginalization technique is a powerful, general tool for addressing many of the challenges facing the precision cosmology programme. [ABSTRACT FROM AUTHOR]

ABSTRACT Decomposing the shear signal into E and B modes properly, i.e. without leakage of B modes into the E-mode signal and vice versa, has been a long-standing problem in weak gravitational lensing. At the two-point level this problem was resolved by developing the so-called ring statistic, and later the COSEBIs; however, extending these concepts to the three-point level is far from trivial. Currently used methods to decompose shear three-point correlation functions (3PCFs) into E and B modes require knowledge of the 3PCF down to arbitrary small scales. This implies that the 3PCF needs to be modelled on scales smaller than the minimum separation of two galaxies and will subsequently be biased towards the model, or, in the absence of a model, the statistic is affected by E-/B-mode leakage (or mixing). In this paper, we derive a new third-order E-/B-mode statistic that performs the decomposition using the 3PCF only on a finite interval, and thereby is free of any E-/B-mode leakage while at the same time relying solely on information from the data. In addition, we relate this third-order ring statistic to the convergence field, thereby enabling a fast and convenient calculation of this statistic from numerical simulations. We note that our new statistic should be applicable to corresponding E-/B-mode separation problems in the cosmic microwave background polarization field. [ABSTRACT FROM AUTHOR]