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Article Dans Une Revue Monthly Notices of the Royal Astronomical Society Année : 2023

Constraining $\nu \Lambda$CDM with density-split clustering

Résumé

The dependence of galaxy clustering on local density provides an effective method for extracting non-Gaussian information from galaxy surveys. The two-point correlation function (2PCF) provides a complete statistical description of a Gaussian density field. However, the late-time density field becomes non-Gaussian due to non-linear gravitational evolution and higher-order summary statistics are required to capture all of its cosmological information. Using a Fisher formalism based on halo catalogues from the Quijote simulations, we explore the possibility of retrieving this information using the density-split clustering (DS) method, which combines clustering statistics from regions of different environmental density. We show that DS provides more precise constraints on the parameters of the $\nu \Lambda$CDM model compared to the 2PCF, and we provide suggestions for where the extra information may come from. DS improves the constraints on the sum of neutrino masses by a factor of $8$ and by factors of 5, 3, 4, 6, and 6 for $\Omega_m$, $\Omega_b$, $h$, $n_s$, and $\sigma_8$, respectively. We compare DS statistics when the local density environment is estimated from the real or redshift-space positions of haloes. The inclusion of DS autocorrelation functions, in addition to the cross-correlation functions between DS environments and haloes, recovers most of the information that is lost when using the redshift-space halo positions to estimate the environment. We discuss the possibility of constructing simulation-based methods to model DS clustering statistics in different scenarios.

Dates et versions

hal-03791552 , version 1 (29-09-2022)

Identifiants

Citer

Enrique Paillas, Carolina Cuesta-Lazaro, Pauline Zarrouk, Yan-Chuan Cai, Will J. Percival, et al.. Constraining $\nu \Lambda$CDM with density-split clustering. Monthly Notices of the Royal Astronomical Society, 2023, 522 (1), pp.606-625. ⟨10.1093/mnras/stad1017⟩. ⟨hal-03791552⟩
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