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The matrix optimum filter for low temperature detectors dead-time reduction

Experiments aiming at high sensitivities usually demand for a very high statistics in order to reach more precise measurements. However, for those exploiting Low Temperature Detectors (LTDs), a high source activity may represent a drawback, if the events rate becomes comparable with the detector cha...

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Detalles Bibliográficos
Autores principales: Borghesi, Matteo, Faverzani, Marco, Ferrari, Cecilia, Ferri, Elena, Giachero, Andrea, Nucciotti, Angelo, Origo, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090876/
https://www.ncbi.nlm.nih.gov/pubmed/35572034
http://dx.doi.org/10.1140/epjc/s10052-022-10379-w
Descripción
Sumario:Experiments aiming at high sensitivities usually demand for a very high statistics in order to reach more precise measurements. However, for those exploiting Low Temperature Detectors (LTDs), a high source activity may represent a drawback, if the events rate becomes comparable with the detector characteristic temporal response. Indeed, since commonly used optimum filtering approaches can only process LTDs signals well isolated in time, a non-negligible part of the recorded experimental data-set is discarded and hence constitute the dead-time. In the presented study we demonstrate that, thanks to the matrix optimum filtering approach, the dead-time of an experiment exploiting LTDs can be strongly reduced.