Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data
Abstract
We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation (emulator) used in the mocks. Importantly, we find a close agreement (<=8% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, making it particularly relevant to the broad current and future analyses of DESI data.
Cite
@article{arxiv.2404.03007,
title = {Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data},
author = {M. Rashkovetskyi and D. Forero-Sánchez and A. de Mattia and D. J. Eisenstein and N. Padmanabhan and H. Seo and A. J. Ross and J. Aguilar and S. Ahlen and O. Alves and U. Andrade and D. Brooks and E. Burtin and X. Chen and T. Claybaugh and S. Cole and A. de la Macorra and Z. Ding and P. Doel and K. Fanning and S. Ferraro and A. Font-Ribera and J. E. Forero-Romero and C. Garcia-Quintero and H. Gil-Marín and S. Gontcho A Gontcho and A. X. Gonzalez-Morales and G. Gutierrez and K. Honscheid and C. Howlett and S. Juneau and A. Kremin and L. Le Guillou and M. Manera and L. Medina-Varela and J. Mena-Fernández and R. Miquel and E. Mueller and A. Muñoz-Gutiérrez and A. D. Myers and J. Nie and G. Niz and E. Paillas and W. J. Percival and C. Poppett and A. Pérez-Fernández and M. Rezaie and A. Rosado-Marin and G. Rossi and R. Ruggeri and E. Sanchez and C. Saulder and D. Schlegel and M. Schubnell and D. Sprayberry and G. Tarlé and B. A. Weaver and J. Yu and C. Zhao and H. Zou},
journal= {arXiv preprint arXiv:2404.03007},
year = {2025}
}
Comments
This DESI Publication is part of the 2024 series using the first year of observations (see https://data.desi.lbl.gov/doc/papers/). 41 pages, 4 figures. Major rewrite after v2. Accepted to JCAP. Code available at https://github.com/oliverphilcox/RascalC and https://github.com/cosmodesi/RascalC-scripts/tree/DESI2024. Figure and table data available at https://zenodo.org/doi/10.5281/zenodo.10895161