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Analytical and EZmock covariance validation for the DESI 2024 results

Forero-Sánchez, D.; Rashkovetskyi, M.; Alves, O.; de Mattia, A.; Padmanabhan, N.; Seo, H.; Nadathur, S.; Ross, A.J.; Gil-Marín, H.; Zarrouk, P.; Yu, J.; Ding, Z.; Andrade, U.; Chen, X.; Garcia-Quintero, C.; Mena-Fernández, J.; Ahlen, S.; Bianchi, D.; Brooks, D.; Burtin, E.; Chaussidon, E.; Claybaugh, T.; Cole, S.; de la Macorra, A.; Enriquez-Vargas, M.; Gaztañaga, E.; Gutierrez, G.; Honscheid, K.; Howlett, C.; Kisner, T.; Landriau, M.; Le Guillou, L.; Levi, M.E.; Miquel, R.; Moustakas, J.; Palanque-Delabrouille, N.; Percival, W.J.; Pérez-Ràfols, I.; Rossi, G.; Sanchez, E.; Schlegel, D.; Schubnell, M.; Sprayberry, D.; Tarlé, G.; Vargas-Magaña, M.; Weaver, B.A.; Zou, H.

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Authors

D. Forero-Sánchez

M. Rashkovetskyi

O. Alves

A. de Mattia

N. Padmanabhan

H. Seo

S. Nadathur

A.J. Ross

H. Gil-Marín

J. Yu

Z. Ding

U. Andrade

X. Chen

C. Garcia-Quintero

J. Mena-Fernández

S. Ahlen

D. Bianchi

D. Brooks

E. Burtin

E. Chaussidon

T. Claybaugh

A. de la Macorra

M. Enriquez-Vargas

E. Gaztañaga

G. Gutierrez

K. Honscheid

C. Howlett

T. Kisner

M. Landriau

L. Le Guillou

M.E. Levi

R. Miquel

J. Moustakas

N. Palanque-Delabrouille

W.J. Percival

I. Pérez-Ràfols

G. Rossi

E. Sanchez

D. Schlegel

M. Schubnell

D. Sprayberry

G. Tarlé

M. Vargas-Magaña

B.A. Weaver

H. Zou



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 an 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 2024 Full Shape analysis.

Citation

Forero-Sánchez, D., Rashkovetskyi, M., Alves, O., de Mattia, A., Padmanabhan, N., Seo, H., Nadathur, S., Ross, A. J., Gil-Marín, H., Zarrouk, P., Yu, J., Ding, Z., Andrade, U., Chen, X., Garcia-Quintero, C., Mena-Fernández, J., Ahlen, S., Bianchi, D., Brooks, D., …Zou, H. (2025). Analytical and EZmock covariance validation for the DESI 2024 results. Journal of Cosmology and Astroparticle Physics, 2025(04), 055. https://doi.org/10.1088/1475-7516/2025/04/055

Journal Article Type Article
Acceptance Date Apr 3, 2025
Online Publication Date Apr 17, 2025
Publication Date 2025-04
Deposit Date May 27, 2025
Publicly Available Date May 27, 2025
Journal Journal of Cosmology and Astroparticle Physics
Electronic ISSN 1475-7516
Publisher IOP Publishing
Peer Reviewed Peer Reviewed
Volume 2025
Issue 04
Article Number 055
DOI https://doi.org/10.1088/1475-7516/2025/04/055
Public URL https://durham-repository.worktribe.com/output/3795820

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