Cosmic void exclusion models and their impact on the distance scale measurements from large-scale structure

Author:

Variu Andrei1ORCID,Zhao Cheng1ORCID,Forero-Sánchez Daniel1ORCID,Chuang Chia-Hsun2,Kitaura Francisco-Shu34,Tao Charling5,Tamone Amélie1,Kneib Jean-Paul1

Affiliation:

1. Institute of Physics, Laboratory of Astrophysics, École Polytechnique Fédérale de Lausanne (EPFL), Observatoire de Sauverny , CH-1290 Versoix , Switzerland

2. Department of Physics and Astronomy, University of Utah , Salt Lake City, UT 84112 , USA

3. Instituto de Astrofísica de Canarias , s/n, E-38205 La Laguna, Tenerife , Spain

4. Departamento de Astrofísica, Universidad de La Laguna , E-38206 La Laguna, Tenerife , Spain

5. CPPM, Aix-Marseille Université , CNRS/IN2P3, CPPM UMR 7346, F-13288 Marseille , France

Abstract

ABSTRACT Baryonic Acoustic Oscillations (BAOs) studies based on the clustering of voids and matter tracers provide important constraints on cosmological parameters related to the expansion of the Universe. However, modelling the void exclusion effect is an important challenge for fully exploiting the potential of this kind of analyses. We thus develop two numerical methods to describe the clustering of cosmic voids. Neither model requires additional cosmological information beyond that assumed within the galaxy de-wiggled model. The models consist in power spectra whose performance we assess in comparison to a parabolic model on Patchy cubic and light-cone mocks. Moreover, we test their robustness against systematic effects and the reconstruction technique. The void model power spectra and the parabolic model with a fixed parameter provide strongly correlated values for the Alcock-Paczynski (α) parameter, for boxes and light-cones likewise. The resulting α values – for all three models – are unbiased and their uncertainties are correctly estimated. However, the numerical models show less variation with the fitting range compared to the parabolic one. The Bayesian evidence suggests that the numerical techniques are often favoured compared to the parabolic model. Moreover, the void model power spectra computed on boxes can describe the void clustering from light-cones as well as from boxes. The same void model power spectra can be used for the study of pre- and post-reconstructed data-sets. Lastly, the two numerical techniques are resilient against the studied systematic effects. Consequently, using either of the two new void models, one can more robustly measure cosmological parameters.

Funder

Swiss National Science Foundation

Tsinghua University

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine learning unveils the linear matter power spectrum of modified gravity;Physical Review D;2024-03-07

2. Mixing bispectrum multipoles under geometric distortions;Monthly Notices of the Royal Astronomical Society;2023-11-02

3. Void BAO measurements on quasars from eBOSS;Monthly Notices of the Royal Astronomical Society;2023-09-22

4. Delfin++: A Delaunay based algorithm for finding 3D polyhedral voids in galaxy surveys;Astronomy and Computing;2023-07

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