arXiv subjects

N. Martini

Publications and source records attributed to N. Martini.

6 recordsLinked to original sources

arXiv2026

Low Energy Phonon Bursts Created By Fast Neutron Damage

Solid state athermal phonon calorimeters used in the search for low mass dark matter or coherent neutrino-nucleus interactions have long observed a large excess of events below several hundred eV. The relaxation of damage created by the interaction of fast cosmic ray neutrons with the detector has been proposed as a source of these excess events. By comparing neutron exposed detectors to control detectors, we report the first measurement of phonon bursts caused by damage created by fast neutrons. Differences in the spectral shape, the rate dependence on thermal history, and the observed spectral rate scaled to the neutron exposure between irradiated and control detectors suggest that our observed LEE backgrounds are not dominated by neutron damage-induced phonon bursts.

physics.ins-det↗

arXiv2023

First demonstration of 30 eVee ionization energy resolution with Ricochet germanium cryogenic bolometers

The future Ricochet experiment aims to search for new physics in the electroweak sector by measuring the Coherent Elastic Neutrino-Nucleus Scattering process from reactor antineutrinos with high precision down to the sub-100 eV nuclear recoil energy range. While the Ricochet collaboration is currently building the experimental setup at the reactor site, it is also finalizing the cryogenic detector arrays that will be integrated into the cryostat at the Institut Laue Langevin in early 2024. In this paper, we report on recent progress from the Ge cryogenic detector technology, called the CryoCube. More specifically, we present the first demonstration of a 30~eVee (electron equivalent) baseline ionization resolution (RMS) achieved with an early design of the detector assembly and its dedicated High Electron Mobility Transistor (HEMT) based front-end electronics. This represents an order of magnitude improvement over the best ionization resolutions obtained on similar heat-and-ionization germanium cryogenic detectors from the EDELWEISS and SuperCDMS dark matter experiments, and a factor of three improvement compared to the first fully-cryogenic HEMT-based preamplifier coupled to a CDMS-II germanium detector. Additionally, we discuss the implications of these results in the context of the future Ricochet experiment and its expected background mitigation performance.

astro-ph.IM↗

arXiv2023

Results from a Prototype TES Detector for the Ricochet Experiment

Coherent elastic neutrino-nucleus scattering (CE$\nu$NS) offers valuable sensitivity to physics beyond the Standard Model. The Ricochet experiment will use cryogenic solid-state detectors to perform a precision measurement of the CE$\nu$NS spectrum induced by the high neutrino flux from the Institut Laue-Langevin nuclear reactor. The experiment will employ an array of detectors, each with a mass of $\sim$30 g and a targeted energy threshold of 50 eV. Nine of these detectors (the "Q-Array") will be based on a novel Transition-Edge Sensor (TES) readout style, in which the TES devices are thermally coupled to the absorber using a gold wire bond. We present initial characterization of a Q-Array-style detector using a 1 gram silicon absorber, obtaining a baseline root-mean-square resolution of less than 40 eV.

physics.ins-det↗

arXiv2023

Tagging and localisation of ionizing events using NbSi transition edge phonon sensors for Dark Matter searches

In the context of direct searches of sub-GeV Dark Matter particles with germanium detectors, the EDELWEISS collaboration has tested a new technique to tag ionizing events using NbSi transition edge athermal phonon sensors. The emission of the athermal phonons generated by the Neganov-Trofimov-Luke effect associated with the drift of electrons and holes through the detectors is used to tag ionization events generated in specific parts of the detector localized in front of the NbSi sensor and to reject by more than a factor 5 (at 90% C.L.) the background from heat-only events that dominates the spectrum above 3 keV. This method is able to improve by a factor 2.8 the previous limit on spin-independent interactions of 1 GeV/c2 WIMPs obtained with the same detector and data set but without this tagging technique.

physics.ins-det↗

arXiv2018

The EUCLID VIS read-out shutter unit: a low disturbance mechanism at cryogenic temperature

Euclid is the second medium-size mission (M2) of the ESA Cosmic Vision Program, currently scheduled for a launch in 2020. The two instruments on-board Euclid, VIS (VISible imager) and NISP (Near Infrared Spectrometer and Photometer), will provide key measurements to investigate the nature of dark energy, advancing our knowledge on cosmology. We present in this contribution the development and manufacturing status of the VIS Read-out Shutter Unit, whose main function is to prevent direct light from falling onto the VIS CCDs during the read-out of the scientific exposures and to allow the dark-current/bias calibrations of the instrument.

astro-ph.IM↗

arXiv2017

An automatic deep learning approach for coronary artery calcium segmentation

Coronary artery calcium (CAC) is a significant marker of atherosclerosis and cardiovascular events. In this work we present a system for the automatic quantification of calcium score in ECG-triggered non-contrast enhanced cardiac computed tomography (CT) images. The proposed system uses a supervised deep learning algorithm, i.e. convolutional neural network (CNN) for the segmentation and classification of candidate lesions as coronary or not, previously extracted in the region of the heart using a cardiac atlas. We trained our network with 45 CT volumes; 18 volumes were used to validate the model and 56 to test it. Individual lesions were detected with a sensitivity of 91.24%, a specificity of 95.37% and a positive predicted value (PPV) of 90.5%; comparing calcium score obtained by the system and calcium score manually evaluated by an expert operator, a Pearson coefficient of 0.983 was obtained. A high agreement (Cohen's k = 0.879) between manual and automatic risk prediction was also observed. These results demonstrated that convolutional neural networks can be effectively applied for the automatic segmentation and classification of coronary calcifications.

cs.CV↗