| Issue |
A&A
Volume 654, October 2021
|
|
|---|---|---|
| Article Number | A95 | |
| Number of page(s) | 5 | |
| Section | Numerical methods and codes | |
| DOI | https://doi.org/10.1051/0004-6361/202141305 | |
| Published online | 18 October 2021 | |
Identification of neutrino bursts associated to supernovae with real-time test statistic (RTS2) method
INFN Sezione di Padova, 35131 Padova, Italy
e-mail: mathieu.lamoureux@pd.infn.it
Received:
13
May
2021
Accepted:
18
July
2021
Aims. This paper proposes a new approach to detecting 𝒪(MeV) neutrino bursts such as those associated with supernovae.
Methods. A novel ‘real-time test statistic’ (RTS) exploits the temporal structure of the expected signal, discriminating against the diffuse background, to allow detection of very weak signals that would elude standard clustering methods.
Results. For a given background rate, the proposed method increases signal efficiency while keeping the same false alarm rate for a Poisson-distributed background. By adding a spatial penalty term to the definition of RTS, it is also possible to reject spatially correlated backgrounds such as those due to spallation events.
Conclusions. The algorithm can be implemented in a real-time monitoring system for detectors of all sizes, allowing prompt alerts to be sent to the wider community, for example through the SNEWS 2.0 network.
Key words: neutrinos / methods: data analysis / methods: statistical / supernovae: general
© M. Lamoureux 2021
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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