Does jackknife scale really matter for accurate large-scale structure covariances?

Abstract

The jackknife method gives an internal covariance estimate for large-scale structure surveys and allows model-independent errors on cosmological parameters. Using the SDSS-III BOSS CMASS sample, we study how the jackknife size and number of resamplings impact the precision of the covariance estimate on the correlation function multipoles and the error on the inferred baryon acoustic scale. We compare the measurement with the MultiDark Patchy mock galaxy catalogues, and we also validate it against a set of log-normal mocks with the same survey geometry. We build several jackknife configurations that vary in size and number of resamplings. We introduce the Hartlap factor in the covariance estimate that depends on the number of jackknife resamplings. We also find that it is useful to apply the tapering scheme to estimate the precision matrix from a limited number of resamplings. The results from CMASS and mock catalogues show that the error estimate of the baryon acoustic scale does not depend on the jackknife scale. For the shift parameter $\alpha$, we find an average error of 1.6%, 2.2% and 1.2%, respectively from CMASS, Patchy and log-normal jackknife covariances. Despite these uncertainties fluctuate significantly due to some structural limitations of the jackknife method, our $\alpha$ estimates are in reasonable agreement with published pre-reconstruction analyses. Jackknife methods will provide valuable and complementary covariance estimates for future large-scale structure surveys.

13 pages, 8 figures, 3 tables

References in corpus (22)

• The EAGLE project: Simulating the evolution and assembly of galaxies and their environments
• The 2.5 m Telescope of the Sloan Digital Sky Survey
• Introducing the Illustris Project: Simulating the coevolution of dark and visible matter in the Universe
• The EAGLE simulations of galaxy formation: calibration of subgrid physics and model variations
• Properties of galaxies reproduced by a hydrodynamic simulation
• Introducing the Illustris Project: the evolution of galaxy populations across cosmic time
• Why your model parameter confidences might be too optimistic -- unbiased estimation of the inverse covariance matrix
• A primer on hierarchical galaxy formation: the semi-analytical approach
• The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Observational systematics and baryon acoustic oscillations in the correlation function
• Constraining Anisotropic Baryon Oscillations
• Metal Enrichment of the ICM: a 3-D Picture of Chemical and Dynamical Properties
• The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Luminosity and Color Dependence and Redshift Evolution
• nIFTy Cosmology: Galaxy/halo mock catalogue comparison project on clustering statistics
• The Stellar Content of Galaxy Halos: A Comparison between LambdaCDM Models and Observations of M31
• Constraining the halo bispectrum in real and redshift space from perturbation theory and non-linear stochastic bias
• Generating Log-normal Mock Catalog of Galaxies in Redshift Space
• Physical drivers of galaxies' cold-gas content: exploring environmental and evolutionary effects with DARK SAGE
• Quantifying distortions of the Lagrangian dark-matter mesh in cosmology
• Modelling The Redshift-Space Three-Point Correlation Function in SDSS-III
• A semi-analytic model comparison: testing cooling models against hydrodynamical simulations
• A new gas cooling model for semi-analytical galaxy formation models
• Cosmological constraints from galaxy multi-tracers in the nearby Universe

Cited by in corpus (13)

• Euclid: Forecasts from redshift-space distortions and the Alcock-Paczynski test with cosmic voids
• Creating Jackknife and Bootstrap estimates of the covariance matrix for the two-point correlation function
• CARPool Covariance: Fast, unbiased covariance estimation for large-scale structure observables
• Cosmology from Cross-Correlation of ACT-DR4 CMB Lensing and DES-Y3 Cosmic Shear
• Galaxy blending effects in deep imaging cosmic shear probes of cosmology
• Bayesian Control Variates for optimal covariance estimation with pairs of simulations and surrogates
• The 2-point correlation function covariance with fewer mocks
• Beyond the Lognormal Approximation: a General Simulation Scheme
• Enhancing Cosmological Model Selection with Interpretable Machine Learning
• Cosmology with voids from the Nancy Grace Roman Space Telescope
• ELG$\times$LRG distribution through dark matter halo dynamics
• Constraining Galaxy-Halo Connection Using Machine Learning
• Three-point intrinsic alignments of galaxies and haloes in the FLAMINGO simulations