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.
Borghesi, M., Faverzani, M., Ferrari, C., Ferri, E., Giachero, A., Nucciotti, A., et al. (2022). The matrix optimum filter for low temperature detectors dead-time reduction. THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS, 82(5 (May 2022)) [10.1140/epjc/s10052-022-10379-w].
The matrix optimum filter for low temperature detectors dead-time reduction
Borghesi M.;Faverzani M.;Ferrari C.
;Ferri E.;Giachero A.;Nucciotti A.;Origo L.
2022
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.