Large Covariance Matrices: Smooth Models from the 2-Point Correlation Function

Abstract

We introduce a new method for estimating the covariance matrix for the galaxy correlation function in surveys of large-scale structure. Our method combines simple theoretical results with a realistic characterization of the survey to dramatically reduce noise in the covariance matrix. For example, with an investment of only ~1,000 CPU hours we can produce a model covariance matrix with noise levels that would otherwise require ~35,000 mocks. Non-Gaussian contributions to the model are calibrated against mock catalogs, after which the model covariance is found to be in impressive agreement with the mock covariance matrix. Since calibration of this method requires fewer mocks than brute force approaches, we believe that it could dramatically reduce the number of mocks required to analyse future surveys.

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• Galaxy Power Spectrum Multipoles Covariance in Perturbation Theory
• Cosmological constraints from BOSS with analytic covariance matrices
• Revealing the galaxy-halo connection in IllustrisTNG
• 2D-FFTLog: Efficient computation of real space covariance matrices for galaxy clustering and weak lensing
• The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: theoretical systematics and Baryon Acoustic Oscillations in the galaxy correlation function
• Comparing approximate methods for mock catalogues and covariance matrices I: correlation function
• Dark matter statistics for large galaxy catalogs: power spectra and covariance matrices
• Fewer Mocks and Less Noise: Reducing the Dimensionality of Cosmological Observables with Subspace Projections
• Perturbation theory approach to predict the covariance matrices of the galaxy power spectrum and bispectrum in redshift space
• The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR16 luminous red galaxy and emission line galaxy samples: cosmic distance and structure growth measurements using multiple tracers in configuration space
• WFIRST Science Investigation Team "Cosmology with the High Latitude Survey" Annual Report 2017
• Power spectrum multipoles on the curved sky: an application to the 6-degree Field Galaxy Survey
• Non-linear shrinkage estimation of large-scale structure covariance
• RascalC: A Jackknife Approach to Estimating Single and Multi-Tracer Galaxy Covariance Matrices
• Super-sample covariance approximations and partial sky coverage
• Likelihood Non-Gaussianity in Large-Scale Structure Analyses
• Galaxy 2-Point Covariance Matrix Estimation for Next Generation Surveys
• Estimating Covariance Matrices for Two- and Three-Point Correlation Function Moments in Arbitrary Survey Geometries
• Disconnected Covariance of 2-point Functions in Large-Scale Structure
• Computing the Small-Scale Galaxy Power Spectrum and Bispectrum in Configuration-Space
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• Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data
• Suppressing cosmic variance with paired-and-fixed cosmological simulations: average properties and covariances of dark matter clustering statistics
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• Analytical and EZmock covariance validation for the DESI 2024 results
• A Faster Fourier Transform? Computing Small-Scale Power Spectra and Bispectra for Cosmological Simulations in $\mathcal{O}(N^2)$ Time
• Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for Early DESI data
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• Fitting covariance matrix models to simulations
• The redshift dependence of Alcock-Paczynski effect: cosmological constraints from the current and next generation observations
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• Faster cosmological analysis with power spectrum without simulations
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• Euclid: Exploring observational systematics in cluster cosmology -- a comprehensive analysis of cluster counts and clustering
• Residual Smoothing: Using Mocks to Correct Model Covariance Matrices