4.6 Article

Tests of neutrino and dark radiation models from galaxy and CMB surveys

出版社

IOP PUBLISHING LTD
DOI: 10.1088/1475-7516/2018/01/022

关键词

cosmological neutrinos; cosmological parameters from LSS; neutrino masses from cosmology

资金

  1. US Department of Energy [DE-SC0007901]
  2. National Science Foundation [PHY-1066293]
  3. U.S. Department of Energy (DOE) [DE-SC0007901] Funding Source: U.S. Department of Energy (DOE)

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We analyze the ability of galaxy and CMB lensing surveys to constrain massive neutrinos and new models of dark radiation. We present a Fisher forecast analysis for neutrino mass constraints with the LSST galaxy survey and the CMB S4 survey. A joint analysis of the three galaxy and shear 2-point functions from LSST, along with key systematics parameters and Planck priors, can constrain the neutrino masses to Sigma m(v) = 0.041 eV at 1-sigma level, comparable to constraints expected from Stage 4 CMB lensing. If low redshift information from upcoming spectroscopic surveys like DESI is included, the constraint becomes Sigma m(v) = 0.032 eV. These constraints are derived having marginalized over the number of relativistic species (N-eff), which is somewhat degenerate with the neutrino mass. We also explore the gain by combining LSST and CMB S4, that is, using the five relevant auto- and cross correlations of the two datasets. We conclude that advances in modeling the nonlinear regime and the measurements of other parameters are required to ensure a neutrino mass detection. Using the same datasets, we explore the ability of LSST-era surveys to test nonstandard models with dark radiation. We find that if evidence for dark radiation is found from Neff measurements, the mass of the dark radiation candidate can be measured at a 1-sigma level of 0.162 eV for fermionic dark radiation, and 0.137 eV for bosonic dark radiation, for Delta N-eff = 0.15. We also find that the NNaturalness model of Arkani-Hamed et al. [1], with extra light degrees of freedom, has a sub-percent effect on the power spectrum: even more ambitious surveys than the ones considered here will be needed to test such models.

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