Nonlinear objects like halos and voids exhibit a scale-dependent bias on linear scales in massive neutrino cosmologies. The shape of this scale-dependent bias is a unique signature of the neutrino masses, but the amplitude of the signal is generally small, of the order of fν, the contribution of neutrinos to the total matter content (≲ 1%). In this paper, we demonstrate for the first time how the strength of this signal can be substantially enhanced by using information about the halo environment at a range of scales. This enhancement is achieved by using certain combinations of the large scale Cold Dark Matter and total matter environments of halos, both of which are measurable from galaxy clustering and weak lensing surveys.

Weighing neutrinos with the halo environment / A. Banerjee, E. Castorina, F. Villaescusa-Navarro, T. Court, M. Viel. - In: JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS. - ISSN 1475-7516. - 2020:6(2020 Jun). [10.1088/1475-7516/2020/06/032]

Weighing neutrinos with the halo environment

E. Castorina
Secondo
;
2020

Abstract

Nonlinear objects like halos and voids exhibit a scale-dependent bias on linear scales in massive neutrino cosmologies. The shape of this scale-dependent bias is a unique signature of the neutrino masses, but the amplitude of the signal is generally small, of the order of fν, the contribution of neutrinos to the total matter content (≲ 1%). In this paper, we demonstrate for the first time how the strength of this signal can be substantially enhanced by using information about the halo environment at a range of scales. This enhancement is achieved by using certain combinations of the large scale Cold Dark Matter and total matter environments of halos, both of which are measurable from galaxy clustering and weak lensing surveys.
cosmological neutrinos; cosmological parameters from LSS; cosmological simulations
Settore FIS/05 - Astronomia e Astrofisica
giu-2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/790184
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