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The matrix optimum filter for low temperature detectors dead-time reduction.
Borghesi, Matteo; Faverzani, Marco; Ferrari, Cecilia; Ferri, Elena; Giachero, Andrea; Nucciotti, Angelo; Origo, Luca.
Afiliação
  • Borghesi M; Dipartimento di Fisica "G. Occhialini", Università di Milano-Bicocca, 20126 Milan, Italy.
  • Faverzani M; INFN-Milano-Bicocca, 20126 Milan, Italy.
  • Ferrari C; Dipartimento di Fisica "G. Occhialini", Università di Milano-Bicocca, 20126 Milan, Italy.
  • Ferri E; INFN-Milano-Bicocca, 20126 Milan, Italy.
  • Giachero A; Gran Sasso Science Institute (GSSI), 67100 L'Aquila, Italy.
  • Nucciotti A; INFN-Laboratori Nazionali del Gran Sasso, Assergi, 67100 L'Aquila, Italy.
  • Origo L; Dipartimento di Fisica "G. Occhialini", Università di Milano-Bicocca, 20126 Milan, Italy.
Eur Phys J C Part Fields ; 82(5): 421, 2022.
Article em En | MEDLINE | ID: mdl-35572034
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.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article