Searching for the Radiative Decay of the Cosmic Neutrino Background with Line-Intensity Mapping

被引:19
|
作者
Bernal, Jose Luis [1 ]
Caputo, Andrea [2 ,3 ,4 ]
Villaescusa-Navarro, Francisco [5 ,6 ]
Kamionkowski, Marc [1 ]
机构
[1] Johns Hopkins Univ, Dept Phys & Astron, 3400 North Charles St, Baltimore, MD 21218 USA
[2] Tel Aviv Univ, Sch Phys & Astron, IL-69978 Tel Aviv, Israel
[3] Weizmann Inst Sci, Dept Particle Phys & Astrophys, IL-7610001 Rehovot, Israel
[4] Werner Heisenberg Inst, Max Planck Inst Phys, Fohringer Ring 6, D-80805 Munich, Germany
[5] Princeton Univ, Dept Astrophys Sci, Peyton Hall, Princeton, NJ 08544 USA
[6] Ctr Computat Astrophys, 162 5th Ave, New York, NY 10010 USA
基金
以色列科学基金会;
关键词
GAUGE-THEORIES; ELECTROMAGNETIC-INTERACTIONS; MAGNETIC-MOMENTS; OSCILLATIONS; FOREGROUNDS; LEPTON; BOUNDS; MODEL; WEAK;
D O I
10.1103/PhysRevLett.127.131102
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We study the possibility to use line-intensity mapping (LIM) to seek photons from the radiative decay of neutrinos in the cosmic neutrino background. The Standard Model prediction for the rate for these decays is extremely small, but it can be enhanced if new physics increases the neutrino electromagnetic moments. The decay photons will appear as an interloper of astrophysical spectral lines. We propose that the neutrinodecay line can be identified with anisotropies in LIM clustering and also with the voxel intensity distribution. Ongoing and future LIM experiments will have-depending on the neutrino hierarchy, transition, and experiment considered-a sensitivity to an effective electromagnetic transition moment similar to 10(-12) - 10(-8) (m(i)c(2)/0.1 eV)(3/2)mu(B), where m(i) is the mass of the decaying neutrino and mu(B) is the Bohr magneton. This will be significantly more sensitive than cosmic microwave background spectral distortions, and it will be competitive with stellar cooling studies. As a by-product, we also report an analytic form of the one-point probability distribution function for neutrino-density fluctuations, obtained from the QUIJOTE simulations using symbolic regression.
引用
收藏
页数:7
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