Published June 29, 2023 | Version Published
Journal Article Open

Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment

Creators

  • 1. ROR icon California Institute of Technology

Abstract

A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the 𝒪⁡(10)  MeV neutrinos produced by a Galactic core-collapse supernova if one should occur during the lifetime of the experiment. The liquid-argon-based detectors planned for DUNE are expected to be uniquely sensitive to the 𝜈𝑒 component of the supernova flux, enabling a wide variety of physics and astrophysics measurements. A key requirement for a correct interpretation of these measurements is a good understanding of the energy-dependent total cross section 𝜎⁡(𝐸𝜈) for charged-current 𝜈𝑒 absorption on argon. In the context of a simulated extraction of supernova 𝜈𝑒 spectral parameters from a toy analysis, we investigate the impact of 𝜎⁡(𝐸𝜈) modeling uncertainties on DUNE’s supernova neutrino physics sensitivity for the first time. We find that the currently large theoretical uncertainties on 𝜎⁡(𝐸𝜈) must be substantially reduced before the 𝜈𝑒 flux parameters can be extracted reliably; in the absence of external constraints, a measurement of the integrated neutrino luminosity with less than 10% bias with DUNE requires 𝜎⁡(𝐸𝜈) to be known to about 5%. The neutrino spectral shape parameters can be known to better than 10% for a 20% uncertainty on the cross-section scale, although they will be sensitive to uncertainties on the shape of 𝜎⁡(𝐸𝜈). A direct measurement of low-energy 𝜈𝑒-argon scattering would be invaluable for improving the theoretical precision to the needed level.

Copyright and License

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.

Acknowledgement

This document was prepared by the DUNE Collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. This work was supported by CNPq, FAPERJ, FAPEG and FAPESP, Brazil; CFI, IPP and NSERC, Canada; CERN; MŠMT, Czech Republic; ERDF, H2020-EU and MSCA, European Union; CNRS/IN2P3 and CEA, France; INFN, Italy; FCT, Portugal; NRF, South Korea; CAM, Fundación “La Caixa,” Junta de Andalucía-FEDER, MICINN, and Xunta de Galicia, Spain; SERI and SNSF, Switzerland; TÜBİTAK, Turkey; The Royal Society and UKRI/STFC, United Kingdom; DOE and NSF, United States of America. This work was also supported by FAPESB T. O. PIE 0013/2016 and UESC/PROPP 0010299-61.

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Additional details

Identifiers

ISSN
2470-0029

Funding

Fermi National Accelerator Laboratory
United States Department of Energy
DE-AC02-07CH11359
Office of Science
Office of High Energy Physics
National Council for Scientific and Technological Development
Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
Fundação de Apoio a Pesquisa do Estado de Goiás
Fundação de Amparo à Pesquisa do Estado de São Paulo
T. O. PIE 0013/2016
Canada Foundation for Innovation
Natural Sciences and Engineering Research Council
European Organization for Nuclear Research
Ministry of Education Youth and Sports
European Commission
European Commission
European Commission
CaixaBank
Junta de Andalucía
Federación Española de Enfermedades Raras
Ministerio de Ciencia, Innovación y Universidades
Xunta de Galicia
Swiss National Science Foundation
Scientific Education and Research Foundation
Centre National de la Recherche Scientifique
Institut National de Physique Nucléaire et de Physique des Particules
Commissariat à l'Énergie Atomique et aux Énergies Alternatives
Istituto Nazionale di Fisica Nucleare
Fundação para a Ciência e Tecnologia
National Research Foundation of Korea
Scientific and Technological Research Council of Turkey
Royal Society
UK Research and Innovation
Science and Technology Facilities Council
National Science Foundation
Universidade Estadual de Santa Cruz
Pró-Reitoria de Pesquisa e Pós-Graduação, Universidade Federal de Ouro Preto
UESC/PROPP 0010299-61
IPP
CAM

Dates

Accepted
2023-05-12
Accepted
Available
2023-06-29
Published online

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Publication Status
Published