Signal processing and spectral modeling for the BeEST experiment
The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay of $^7$Be by precisely measuring the recoil energy of the $^7$Li daughter. In Phase-III, the BeEST experiment has been...
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Format | Journal Article |
Language | English |
Published |
27.09.2024
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Subjects | |
Online Access | Get full text |
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Summary: | The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST)
experiment searches for evidence of heavy neutrino mass eigenstates in the
nuclear electron capture decay of $^7$Be by precisely measuring the recoil
energy of the $^7$Li daughter. In Phase-III, the BeEST experiment has been
scaled from a single superconducting tunnel junction (STJ) sensor to a 36-pixel
array to increase sensitivity and mitigate gamma-induced backgrounds. Phase-III
also uses a new continuous data acquisition system that greatly increases the
flexibility for signal processing and data cleaning. We have developed
procedures for signal processing and spectral fitting that are sufficiently
robust to be automated for large data sets. This article presents the optimized
procedures before unblinding the majority of the Phase-III data set to search
for physics beyond the standard model. |
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DOI: | 10.48550/arxiv.2409.19085 |