Signal processing and spectral modeling for the BeEST experiment
Abstract
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 Be by precisely measuring the recoil energy of the 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.
Cite
@article{arxiv.2409.19085,
title = {Signal processing and spectral modeling for the BeEST experiment},
author = {Inwook Kim and Connor Bray and Andrew Marino and Caitlyn Stone-Whitehead and Amii Lamm and Ryan Abells and Pedro Amaro and Adrien Andoche and Robin Cantor and David Diercks and Spencer Fretwell and Abigail Gillespie and Mauro Guerra and Ad Hall and Cameron N. Harris and Jackson T. Harris and Calvin Hinkle and Leendert M. Hayen and Paul-Antoine Hervieux and Geon-Bo Kim and Kyle G. Leach and Annika Lennarz and Vincenzo Lordi and Jorge Machado and David McKeen and Xavier Mougeot and Francisco Ponce and Chris Ruiz and Amit Samanta and José Paulo Santos and Joseph Smolsky and John Taylor and Joseph Templet and Sriteja Upadhyayula and Louis Wagner and William K. Warburton and Benjamin Waters and Stephan Friedrich},
journal= {arXiv preprint arXiv:2409.19085},
year = {2025}
}