Efficient computation of the super-sample covariance for stage IV galaxy surveys
arXiv:2209.14421 · doi:10.1051/0004-6361/202245148
Abstract
Super-sample covariance (SSC) is an important effect for cosmological analyses that use the deep structure of the cosmic web; it may, however, be nontrivial to include it practically in a pipeline. We solve this difficulty by presenting a formula for the precision (inverse covariance) matrix and show applications to update likelihood or Fisher forecast pipelines. The formula has several advantages in terms of speed, reliability, stability, and ease of implementation. We present an analytical application to show the formal equivalence between three approaches to SSC: (i) at the usual covariance level, (ii) at the likelihood level, and (iii) with a quadratic estimator. We then present an application of this computationally efficient framework for studying the impact of inaccurate modelling of SSC responses for cosmological constraints from stage IV surveys. We find that a weak-lensing-only analysis is very sensitive to inaccurate modelling of the scale dependence of the response, which needs to be calibrated at the level. The sensitivity to this scale dependence is less severe for the joint weak-lensing and galaxy clustering analysis (also known as 3x2pt). Nevertheless, we find that both the amplitude and scale-dependence of the responses have to be calibrated at better than 30\%.
arXiv comment12+2 pages, 5 figures. Version published in A&A
References in corpus (35)
- Astropy: A Community Python Package for Astronomy
- Binary companions of evolved stars in APOGEE DR14: Search method and catalog of ~5,000 companions
- The Cosmic Linear Anisotropy Solving System (CLASS) II: Approximation schemes
- Revising the Halofit Model for the Nonlinear Matter Power Spectrum
- KiDS-450: Cosmological parameter constraints from tomographic weak gravitational lensing
- MASTER of the CMB Anisotropy Power Spectrum: A Fast Method for Statistical Analysis of Large and Complex CMB Data Sets
- Dark energy constraints from cosmic shear power spectra: impact of intrinsic alignments on photometric redshift requirements
- CMB Lensing Reconstruction on the Full Sky
- Sample Variance Considerations for Cluster Surveys
- Massive Neutrinos and the Non-linear Matter Power Spectrum
- CosmoSIS: modular cosmological parameter estimation
- Intrinsic galaxy alignments from the 2SLAQ and SDSS surveys: luminosity and redshift scalings and implications for weak lensing surveys
- Power Spectrum Super-Sample Covariance
- Galaxy Power Spectrum Multipoles Covariance in Perturbation Theory
- Super-Sample Signal
- Accurate cosmic shear errors: do we need ensembles of simulations?
- Complete super-sample lensing covariance in the response approach
- Joint analysis of cluster number counts and weak lensing power spectrum to correct for the super-sample covariance
- Responses in Large-Scale Structure
- Euclid: The importance of galaxy clustering and weak lensing cross-correlations within the photometric Euclid survey
- Galaxy power-spectrum responses and redshift-space super-sample effect
- Bispectrum Supersample Covariance
- Combining cluster number counts and galaxy clustering
- Super-sample covariance approximations and partial sky coverage
- Fast and easy super-sample covariance of large scale structure observables
- Covariance of the galaxy angular power spectrum with the halo model
- An optimal survey geometry of weak lensing survey: minimizing super-sample covariance
- Debiasing inference with approximate covariance matrices and other unidentified biases
- Density reconstruction from biased tracers and its application to primordial non-Gaussianity
- Inadequacy of internal covariance estimation for super-sample covariance
- Effects of Completeness and Purity on Cluster Dark Energy Constraints
- Impact of survey geometry and super-sample covariance on future photometric galaxy surveys
- Large Scale Structure Reconstruction with Short-Wavelength Modes
- The impact of braiding covariance and in-survey covariance on next-generation galaxy surveys
- Forecasting Super-Sample Covariance in Future Weak Lensing Surveys with SuperSCRAM