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Cosmological constraints from density-split clustering in the BOSS CMASS galaxy sample

Title: Cosmological constraints from density-split clustering in the BOSS CMASS galaxy sample
Authors: Paillas, Enrique; Cuesta-Lazaro, Carolina; Percival, Will J; Nadathur, Seshadri; Cai, Yan-Chuan; Yuan, Sihan; Beutler, Florian; de Mattia, Arnaud; Eisenstein, Daniel J; Forero-Sanchez, Daniel; Padilla, Nelson; Pinon, Mathilde; Ruhlmann-Kleider, Vanina; Sánchez, Ariel G; Valogiannis, Georgios; Zarrouk, Pauline
Contributors: Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency; STFC; European Research Council; ERC; Horizon 2020; Royal Society
Source: Monthly Notices of the Royal Astronomical Society ; volume 531, issue 1, page 898-918 ; ISSN 0035-8711 1365-2966
Publisher Information: Oxford University Press (OUP)
Publication Year: 2024
Description: We present a clustering analysis of the BOSS DR12 CMASS galaxy sample, combining measurements of the galaxy two-point correlation function and density-split clustering down to a scale of $1 \, h^{-1}\, \text{Mpc}$. Our theoretical framework is based on emulators trained on high-fidelity mock galaxy catalogues that forward model the cosmological dependence of the clustering statistics within an extended-ΛCDM framework, including redshift-space and Alcock–Paczynski distortions. Our base-ΛCDM analysis finds ωcdm = 0.1201 ± 0.0022, σ8 = 0.792 ± 0.034, and ns = 0.970 ± 0.018, corresponding to fσ8 = 0.462 ± 0.020 at z ≈ 0.525, which is in agreement with Planck 2018 predictions and various clustering studies in the literature. We test single-parameter extensions to base-ΛCDM, varying the running of the spectral index, the dark energy equation of state, and the density of mass-less relic neutrinos, finding no compelling evidence for deviations from the base model. We model the galaxy–halo connection using a halo occupation distribution framework, finding signatures of environment-based assembly bias in the data. We validate our pipeline against mock catalogues that match the clustering and selection properties of CMASS, showing that we can recover unbiased cosmological constraints even with a volume 84 times larger than the one used in this study.
Document Type: article in journal/newspaper
Language: English
DOI: 10.1093/mnras/stae1118
DOI: 10.1093/mnras/stae1118/57335218/stae1118.pdf
DOI: 10.1093/mnras/stae1118/57768718/stae1118.pdf
Availability: https://doi.org/10.1093/mnras/stae1118; https://academic.oup.com/mnras/advance-article-pdf/doi/10.1093/mnras/stae1118/57335218/stae1118.pdf; https://academic.oup.com/mnras/advance-article-pdf/doi/10.1093/mnras/stae1118/57768718/stae1118.pdf
Rights: https://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.B9CD9B10
Database: BASE