Exploring HOD-dependent systematics for the DESI 2024 Full-Shape galaxy clustering analysis

Abstract

We analyse the robustness of the DESI 2024 cosmological inference from the full shape of the galaxy power spectrum to uncertainties in the Halo Occupation Distribution (HOD) model of the galaxy-halo connection and the choice of priors on nuisance parameters. We assess variations in the recovered cosmological parameters across a range of mocks populated with different HOD models and find that shifts are often greater than 20% of the expected statistical uncertainties from the DESI data. We encapsulate the effect of such shifts in terms of a systematic covariance term, ${\mathsf{C}}_{\mathrm{HOD}}$, and an additional diagonal contribution quantifying the impact of our choice of nuisance parameter priors on the ability of the effective field theory (EFT) model to correctly recover the cosmological parameters of the simulations. These two covariance contributions are designed to be added to the usual covariance term, ${\mathsf{C}}_{\mathrm{stat}}$, describing the statistical uncertainty in the power spectrum measurement, in order to fairly represent these sources of systematic uncertainty. This novel approach should be more general and robust to the choice of model or additional external datasets used in cosmological fits than the alternative approach of adding systematic uncertainties to the recovered marginalised parameter posteriors. We compare the approaches within the context of a fixed $\Lambda$CDM model and demonstrate that our method gives conservative estimates of the systematic uncertainty that nevertheless have little impact on the final posteriors obtained from DESI data.

This DESI Collaboration Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers/). 31 pages, 11 figures. Published in JCAP

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Cited by in corpus (2)

• DESI 2024 VII: Cosmological Constraints from the Full-Shape Modeling of Clustering Measurements
• DESI 2024 V: Full-Shape Galaxy Clustering from Galaxies and Quasars