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Title: Robust measurement of supernova ν e spectra with future neutrino detectors

Abstract

Measuring precise all-flavor neutrino information from a supernova is crucial for understanding the core-collapse process as well as neutrino properties. We apply a chi-squared analysis for different detector setups to explore determination of νe spectral parameters. Using a long-term two-dimensional core-collapse simulation with three time-varying spectral parameters, we generate mock data to examine the capabilities of the current Super-Kamiokande detector and compare the relative improvements that gadolinium, Hyper-Kamiokande, and DUNE would have. We show that in a realistic three spectral parameter framework, the addition of gadolinium to Super-Kamiokande allows for a qualitative improvement in νe determination. Efficient neutron tagging will allow Hyper-Kamiokande to constrain spectral information more strongly in both the accretion and cooling phases. Overall, significant improvements will be made by Hyper-Kamiokande and DUNE, allowing for much more precise determination of νe spectral parameters.

Authors:
 [1];  [2];  [3]
  1. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Dept. of Physics
  2. Stanford Univ., CA (United States). Kavli Inst. for Particle Astrophysics and Cosmology, Dept. of Physics
  3. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Center for Neutrino Physics, Dept. of Physics
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE; German Research Foundation (DFG); European Union (EU)
OSTI Identifier:
1424724
Alternate Identifier(s):
OSTI ID: 1418081
Grant/Contract Number:  
AC02-76SF00515; EXC-1098; KO 4820/1-1; FOR 2239; 637506; SC0018327
Resource Type:
Accepted Manuscript
Journal Name:
Physical Review D
Additional Journal Information:
Journal Volume: 97; Journal Issue: 2; Journal ID: ISSN 2470-0010
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS

Citation Formats

Nikrant, Alex, Laha, Ranjan, and Horiuchi, Shunsaku. Robust measurement of supernova νe spectra with future neutrino detectors. United States: N. p., 2018. Web. doi:10.1103/physrevd.97.023019.
Nikrant, Alex, Laha, Ranjan, & Horiuchi, Shunsaku. Robust measurement of supernova νe spectra with future neutrino detectors. United States. doi:10.1103/physrevd.97.023019.
Nikrant, Alex, Laha, Ranjan, and Horiuchi, Shunsaku. Thu . "Robust measurement of supernova νe spectra with future neutrino detectors". United States. doi:10.1103/physrevd.97.023019. https://www.osti.gov/servlets/purl/1424724.
@article{osti_1424724,
title = {Robust measurement of supernova νe spectra with future neutrino detectors},
author = {Nikrant, Alex and Laha, Ranjan and Horiuchi, Shunsaku},
abstractNote = {Measuring precise all-flavor neutrino information from a supernova is crucial for understanding the core-collapse process as well as neutrino properties. We apply a chi-squared analysis for different detector setups to explore determination of νe spectral parameters. Using a long-term two-dimensional core-collapse simulation with three time-varying spectral parameters, we generate mock data to examine the capabilities of the current Super-Kamiokande detector and compare the relative improvements that gadolinium, Hyper-Kamiokande, and DUNE would have. We show that in a realistic three spectral parameter framework, the addition of gadolinium to Super-Kamiokande allows for a qualitative improvement in νe determination. Efficient neutron tagging will allow Hyper-Kamiokande to constrain spectral information more strongly in both the accretion and cooling phases. Overall, significant improvements will be made by Hyper-Kamiokande and DUNE, allowing for much more precise determination of νe spectral parameters.},
doi = {10.1103/physrevd.97.023019},
journal = {Physical Review D},
number = 2,
volume = 97,
place = {United States},
year = {2018},
month = {1}
}

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Cited by: 8 works
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