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Title: Tree-level bispectrum in the effective field theory of large-scale structure extended to massive neutrinos

Abstract

We compute the tree-level bispectrum of dark matter in the presence of massive neutrinos in the mildly non-linear regime in the context of the effective field theory of large-scale structure (EFTofLSS) . For neutrinos, whose typical free streaming wavenumber (k fs) is longer than the non-linear scale (k NL), we solve a Boltzmann equation coupled to the effective fluid equation for dark matter. We solve perturbatively the coupled system by expanding in powers of the neutrino density fraction (fν) and the ratio of the wavenumber of interest over the non-linear scale (k/k NL) and add suitable counterterms to remove the dependence from short distance physics. For equilateral configurations, we find that the total-matter tree-level bispectrum is approximately 16fν times the dark matter one on short scales (k > k fs). The largest contribution stems from the back-reaction of massive neutrinos on the dark matter growth factor. As a result, on large scales (k < k fs) the contribution of neutrinos to the bispectrum is smaller by up to two orders of magnitude.

Authors:
 [1];  [2]
  1. ETH Zurich, Zurich (Switzerland); Stanford Univ., Stanford, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States)
  2. Stanford Univ., Stanford, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States)
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1507028
Grant/Contract Number:  
AC02-76SF00515
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Cosmology and Astroparticle Physics
Additional Journal Information:
Journal Volume: 2019; Journal Issue: 02; Journal ID: ISSN 1475-7516
Publisher:
Institute of Physics (IOP)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; cosmology; large-scale structure; neutrinos

Citation Formats

de Belsunce, Roger, and Senatore, Leonardo. Tree-level bispectrum in the effective field theory of large-scale structure extended to massive neutrinos. United States: N. p., 2019. Web. doi:10.1088/1475-7516/2019/02/038.
de Belsunce, Roger, & Senatore, Leonardo. Tree-level bispectrum in the effective field theory of large-scale structure extended to massive neutrinos. United States. doi:10.1088/1475-7516/2019/02/038.
de Belsunce, Roger, and Senatore, Leonardo. Mon . "Tree-level bispectrum in the effective field theory of large-scale structure extended to massive neutrinos". United States. doi:10.1088/1475-7516/2019/02/038.
@article{osti_1507028,
title = {Tree-level bispectrum in the effective field theory of large-scale structure extended to massive neutrinos},
author = {de Belsunce, Roger and Senatore, Leonardo},
abstractNote = {We compute the tree-level bispectrum of dark matter in the presence of massive neutrinos in the mildly non-linear regime in the context of the effective field theory of large-scale structure (EFTofLSS) . For neutrinos, whose typical free streaming wavenumber (kfs) is longer than the non-linear scale (kNL), we solve a Boltzmann equation coupled to the effective fluid equation for dark matter. We solve perturbatively the coupled system by expanding in powers of the neutrino density fraction (fν) and the ratio of the wavenumber of interest over the non-linear scale (k/kNL) and add suitable counterterms to remove the dependence from short distance physics. For equilateral configurations, we find that the total-matter tree-level bispectrum is approximately 16fν times the dark matter one on short scales (k > kfs). The largest contribution stems from the back-reaction of massive neutrinos on the dark matter growth factor. As a result, on large scales (k < kfs) the contribution of neutrinos to the bispectrum is smaller by up to two orders of magnitude.},
doi = {10.1088/1475-7516/2019/02/038},
journal = {Journal of Cosmology and Astroparticle Physics},
number = 02,
volume = 2019,
place = {United States},
year = {2019},
month = {2}
}

Journal Article:
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This content will become publicly available on February 18, 2020
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