arXiv subjects

L. Pierini

Publications and source records attributed to L. Pierini.

3 recordsLinked to original sources

arXiv2025

Cryogenic characterization of FBK NUV-HD-Cryo 3T SiPM sensors for the DUNE photon detection system

The Deep Underground Neutrino Experiment (DUNE) is a long-baseline neutrino experiment based in the USA and composed of a Near Detector (ND) complex at Fermi National Laboratory (FNAL), and a Far Detector (FD) complex located at the Sanford Underground Research Facility (SURF) $\sim$1300\,km distant. DUNE will study neutrino oscillations looking for unresolved issues of the Standard Model of particle physics (SM) such as CP violation in the leptonic sector, neutrino mass ordering and others, starting from the early 2030s. The FD, with a mass of $\sim$17\,kt, that will exploit both ionization and scintillation signals to detect neutrino interactions with Argon. Scintillating photons in LAr will be detected by the photon detection system (PDS) based on light collectors coupled to Silicon Photomultipliers (SiPMs). During a test campaign, different laboratories of the collaboration performed an investigation of the best SiPM candidates that fulfill the DUNE FD requirements. We identified two models of SiPM, produced by Hamamatsu Photonics K.K. (HPK) and Fondazione Bruno Kessler (FBK), respectively. In this paper, we focus on the FBK selected model showing its main features. We will describe the characterization protocol, the results at both room and cryogenic temperatures and the photon detection efficiency measurements.

physics.ins-det↗

arXiv2024

Two sides of the same coin: the F-statistic and the 5-vector method

This work explores the relationship between two data-analysis methods used in the search for continuous gravitational waves in LIGO-Virgo-KAGRA data: the $\mathcal{F}$-statistic and the 5-vector method. We show that the 5-vector method can be derived from a maximum likelihood framework similar to the $\mathcal{F}$-statistic. Our analysis demonstrates that the two methods are statistically equivalent, providing the same detection probability for a given false alarm rate. We extend this comparison to multiple detectors, highlighting differences from the standard approach that simply combines 5-vectors from each detector. In our maximum likelihood approach, each 5-vector is weighted by the observation time and sensitivity of its respective detector, resulting in efficient estimators and analytical distributions for the detection statistic. Additionally, we present the analytical computation of sensitivity for different searches, expressed in terms of the minimum detectable amplitude.

gr-qc↗

arXiv2023

A semi-coherent generalization of the 5-vector method to search for continuous gravitational waves

The emission of continuous gravitational waves (CWs), with duration much longer than the typical data taking runs, is expected from several sources, notably spinning neutron stars, asymmetric with respect to their rotation axis and more exotic sources, like ultra-light scalar boson clouds formed around Kerr black holes and sub-solar mass primordial binary black holes. Unless the signal time evolution is well predicted and its relevant parameters accurately known, the search for CWs is typically based on semi-coherent methods, where the full data set is divided in shorter chunks of given duration, which are properly processed, and then incoherently combined. In this paper we present a semi-coherent method, in which the so-called \textit{5-vector} statistics is computed for the various data segments and then summed after the removal of the Earth Doppler modulation and signal intrinsic spin-down. The method can work with segment duration of several days, thanks to a double stage procedure in which an initial rough correction of the Doppler and spin-down is followed by a refined step in which the residual variations are removed. This method can be efficiently applied for directed searches, where the source position is known to a good level of accuracy, and in the candidate follow-up stage of wide-parameter space searches.

gr-qc↗