Residual Smoothing: Using Mocks to Correct Model Covariance Matrices

2019/11/12 by O'Connell, Ross · 1 citation
#Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences

paper · doi:10.48550/arxiv.1911.04670

Abstract

Abstract Covariance matrix estimation is a challenging problem in cosmology. Recent work has shown that model covariance matrices can be precise, and that at relatively large scales they can also be accurate. We introduce a data-driven method that can identify features from a mock covariance matrix that are missing from a corresponding model, then incorporate them into the model without significantly degrading the model's precision. We apply this method to a BOSS-like survey and extend a model covariance to be valid at scales relevant for measurements of Redshift Space Distortions (8-40 Mpc/h), where the galaxy field is significantly non-Gaussian.

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