Analytical and EZmock covariance validation for the DESI 2024 results

Abstract

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full Shape, two approaches are usually considered. First: analytical estimates of the covariance matrix use Gaussian approximations and (nonlinear) clustering measurements to estimate the matrix, which allows a relatively fast and computationally cheap way to generate matrices that adapt to an arbitrary clustering measurement. On the other hand, sample covariances are an empirical estimate of the matrix based on en ensemble of clustering measurements from fast and approximate simulations. While more computationally expensive due to the large amount of simulations and volume required, these allow us to take into account systematics that are impossible to model analytically. In this work we compare these two approaches in order to enable DESI's key analyses. We find that the configuration space analytical estimate performs satisfactorily in BAO analyses and its flexibility in terms of input clustering makes it the fiducial choice for DESI's 2024 BAO analysis. On the contrary, the analytical computation of the covariance matrix in Fourier space does not reproduce the expected measurements in terms of Full Shape analyses, which motivates the use of a corrected mock covariance for DESI's Full Shape analysis.

arXiv comment24 pages, 5 figures 7 tables, accepted to JCAP

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• DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars
• DESI 2024 VII: Cosmological Constraints from the Full-Shape Modeling of Clustering Measurements
• DESI 2024 II: Sample Definitions, Characteristics, and Two-point Clustering Statistics
• DESI 2024 V: Full-Shape Galaxy Clustering from Galaxies and Quasars
• Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data
• Fiducial-Cosmology-dependent systematics for the DESI 2024 BAO Analysis
• $H_0$ Without the Sound Horizon (or Supernovae): A 2% Measurement in DESI DR1
• Exploring HOD-dependent systematics for the DESI 2024 Full-Shape galaxy clustering analysis
• Inference of matter power spectrum at z=0 using DESI DR1 Full-Shape data
• An analytic approximation to the covariance between pre- and post-reconstruction galaxy two-point statistics
• Parity-odd Four-Point Correlation Function from DESI Data Release 1 Luminous Red Galaxy Sample