• Open Access

Model-independent approach to the reconstruction of multiflavor supernova neutrino energy spectra

Hui-Ling Li, Xin Huang, Yu-Feng Li, Liang-Jian Wen, and Shun Zhou
Phys. Rev. D 99, 123009 – Published 11 June 2019

Abstract

The model-independent reconstruction of the energy spectra of ν¯e, νe, and νx (i.e., νμ, ντ, and their antiparticles) from the future observation of a galactic core-collapse supernova (SN) is of crucial importance to understand the microscopic physics of SN explosions. To this end, we propose a practically useful method to combine the multichannel detection of SN neutrinos in a large liquid-scintillator detector (e.g., JUNO), namely, the inverse beta decay ν¯e+pe++n, the elastic neutrino-proton scattering ν+pν+p and the elastic neutrino-electron scattering ν+eν+e, and reconstruct the energy spectra of ν¯e, νe, and νx by making the best use of the observational data in those three channels. In addition, the neutrino energy spectra from the numerical simulations of the delayed neutrino-driven SN explosions are implemented to demonstrate the robustness of our method. Taking the ordinary matter effects into account, we also show how to extract the initial neutrino energy spectra in the presence of neutrino flavor conversions.

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  • Received 13 March 2019

DOI:https://doi.org/10.1103/PhysRevD.99.123009

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3.

Published by the American Physical Society

Physics Subject Headings (PhySH)

  1. Physical Systems
Particles & FieldsGravitation, Cosmology & Astrophysics

Authors & Affiliations

Hui-Ling Li1,*, Xin Huang1,2,†, Yu-Feng Li1,2,‡, Liang-Jian Wen1,§, and Shun Zhou1,2,∥

  • 1Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
  • 2School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China

  • *lihuiling@ihep.ac.cn
  • huangxin@ihep.ac.cn
  • liyufeng@ihep.ac.cn
  • §wenlj@ihep.ac.cn
  • zhoush@ihep.ac.cn

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Issue

Vol. 99, Iss. 12 — 15 June 2019

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