Claudio Piemonte | Searcharxiv

arXiv2023

SiPM Signal Processing via Multiple Linear Regression

This paper presents a novel approach using multiple linear regression to process transient signals from silicon photomultipliers. The method provides excellent noise suppression and pulse detection in scenarios with a high pulse count rate and superimposed pulses. Insights into its implementation and benchmark results are presented. We also show how this approach can be used to automatically detect the pulse shape from a given transient signal, providing good detection for count rates up to 90MHz. Experimental data are used to present an application where this algorithm improves charge spectrum resolution by an order of magnitude.

physics.ins-det↗

arXiv2016

Cryogenic Characterization of FBK HD Near-UV Sensitive SiPMs

We report on the characterization of near-ultraviolet high density silicon photomultiplier (\SiPM) developed at Fondazione Bruno Kessler (\FBK) at cryogenic temperature. A dedicated setup was built to measure the primary dark noise and correlated noise of the \SiPMs\ between 40 and 300~K. Moreover, an analysis program and data acquisition system were developed to allow the precise characterization of these parameters, some of which can vary up to 7 orders of magnitude between room temperature and 40~K. We demonstrate that it is possible to operate the \FBK\ near-ultraviolet high density \SiPMs\ at temperatures lower than 100~K with a dark rate below 0.01 cps/mm$^2$ and total correlated noise probability below 35\% at an over-voltage of 6~V. These results are relevant for the development of future cryogenic particle detectors using \SiPMs\ as photosensors.

physics.ins-det↗