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CUPID-0 is the first large mass array of enriched Zn\\[^{82}\\]Se scintillating low temperature calorimeters, operated at LNGS since 2017. During its first scientific runs, CUPID-0 collected an exposure of 9.95 kg year. Thanks to the excellent rejection of \\[\\alpha \\] particles, we attained the lowest background ever measured with thermal detectors in the energy region where we search for the signature of \\[^{82}\\hbox {Se}\\] neutrinoless double beta decay. In this work we develop a model to reconstruct the CUPID-0 background over the whole energy range of experimental data. We identify the background sources exploiting their distinctive signatures and we assess their extremely low contribution [down to \\[\\sim 10^{-4}\\] counts/(keV kg year)] in the region of interest for \\[^{82}\\hbox {Se}\\] neutrinoless double beta decay search. This result represents a crucial step towards the comprehension of the background in experiments based on scintillating calorimeters and in next generation projects such as CUPID.

Radioactivity was recently discovered as a source of decoherence and correlated errors for the real-world implementation of superconducting quantum processors. In this work, we measure levels of radioactivity present in a typical laboratory environment (from muons, neutrons, and γ -rays emitted by naturally occurring radioactive isotopes) and in the most commonly used materials for the assembly and operation of state-of-the-art superconducting qubits. We present a GEANT-4 based simulation to predict the rate of impacts and the amount of energy released in a qubit chip from each of the mentioned sources. We finally propose mitigation strategies for the operation of next-generation qubits in a radio-pure environment.

The suppression of spurious events in the region of interest for neutrinoless double beta decay will play a major role in next generation experiments. The background of detectors based on the technology of cryogenic calorimeters is expected to be dominated by \\[\\alpha \\] particles, that could be disentangled from double beta decay signals by exploiting the difference in the emission of the scintillation light. CUPID-0, an array of enriched Zn\\[^{82}\\]Se scintillating calorimeters, is the first large mass demonstrator of this technology. The detector started data-taking in 2017 at the Laboratori Nazionali del Gran Sasso with the aim of proving that dual read-out of light and heat allows for an efficient suppression of the \\[\\alpha \\] background. In this paper we describe the software tools we developed for the analysis of scintillating calorimeters and we demonstrate that this technology allows to reach an unprecedented background for cryogenic calorimeters.

High Purity Germanium (HPGe) detectors are powerful detectors for gamma-ray spectroscopy. The sensitivity to low-intensity gamma-ray peaks is often hindered by the presence of Compton continuum distributions, originated by gamma-rays emitted at higher energies. This study explores novel, pulse shape-based, machine learning-assisted techniques to enhance Compton background discrimination in Broad Energy Germanium (BEGe™) detectors. We introduce two machine learning models: an autoencoder-MLP (Multilayer Perceptron) and a Gaussian Mixture Model (GMM). These models differentiate single-site events (SSEs) from multi-site events (MSEs) and train on signal waveforms produced in the detector. The GMM method differs from previous machine learning efforts in that it is fully unsupervised, hence not requiring specific data labelling during the training phase. Being both label-free and simulation-agnostic makes the unsupervised approach particularly advantageous for tasks where realistic, high-fidelity labeling is challenging or where biases introduced by simulated data must be avoided. In our analysis, the full-energy Peak-to-Compton ratio of the 137 Cs, a radionuclide contained in a cryoconite sample, exhibits an improvement from 0.238 in the original spectrum to 0.547 after the ACM data filtering and 0.414 after the GMM data filtering, demonstrating the effectiveness of these methods. The results also showcase an enhancement in the signal-to-background ratio across many regions of interest, enabling the detection of lower concentrations of radionuclides.

In the framework of rare event searches, the identification of radioactive contaminants in ultra-pure samples is a challenging task, because the signal is often at the same level of the instrumental background. This is a rather common situation for α-spectrometers and other detectors used for low-activity measurements. In order to obtain the target sensitivity without extending the data taking live-time, analysis strategies that highlight the presence of the signal sought should be developed. In this paper, we show how to improve the contaminant tagging capability relying on the time-correlation of radioactive decay sequences. We validate the proposed technique by measuring the impurity level of both contaminated and ultra-pure copper samples, demonstrating the potential of this analysis tool in disentangling different background sources and providing an effective way to mitigate their impact in rare event searches.

The CUPID-0 experiment searches for double beta decay using cryogenic calorimeters with double (heat and light) read-out. The detector, consisting of 24 ZnSe crystals 95\\[\\%\\] enriched in \\[^{82}\\]Se and two natural ZnSe crystals, started data-taking in 2017 at Laboratori Nazionali del Gran Sasso. We present the search for the neutrino-less double beta decay of \\[^{82}\\]Se into the 0\\[_1^+\\], 2\\[_1^+\\] and 2\\[_2^+\\] excited states of \\[^{82}\\]Kr with an exposure of 5.74 kg\\[\\cdot \\]yr (2.24\\[\\times \\]10\\[^{25}\\] emitters\\[\\cdot \\]yr). We found no evidence of the decays and set the most stringent limits on the widths of these processes: \\[\\varGamma \\](\\[^{82}\\]Se \\[\\rightarrow ^{82}\\]Kr\\[_{0_1^+}\\])8.55\\[\\times \\]10\\[^{-24}\\] yr\\[^{-1}\\], \\[\\varGamma \\] (\\[^{82}\\] Se \\[\\rightarrow ^{82}\\] Kr \\[_{2_1^+}\\])\\[\\,{<}\\,6.25 \\,{\\times }\\,10^{-24}\\] yr\\[^{-1}\\], \\[\\varGamma \\](\\[^{82}\\]Se \\[\\rightarrow ^{82}\\]Kr\\[_{2_2^+}\\])8.25\\[\\times \\]10\\[^{-24}\\] yr\\[^{-1}\\] (90\\[\\%\\] credible interval).

Localization and modeling of radioactive contaminations is a challenge that ultra-low background experiments are constantly facing. These are fundamental steps both to extract scientific results and to further reduce the background of the detectors. Here we present an innovative technique based on the analysis of α-α delayed coincidences in 232Th and 238U decay chains, developed to investigate the contaminations of the ZnSe crystals in the CUPID-0 experiment. This method allows to disentangle surface and bulk contaminations of the detectors relying on the different probability to tag delayed coincidences as function of the α decay position.

This study investigates the microstructural evolution and mechanical response of sputter-deposited amorphous silicon oxycarbide (SiOC)/crystalline Fe nanolaminates, a single layer SiOC film, and a single layer Fe film subjected to ion implantation at room temperature to obtain a maximum He concentration of 5 at. %. X-ray diffraction and transmission electron microscopy indicated no evidence of implantation-induced phase transformation or layer breakdown in the nanolaminates. Implantation resulted in the formation of He bubbles and an increase in the average size of the Fe grains in the individual Fe layers of the nanolaminates and the single layer Fe film, but the bubble density and grain size were found to be smaller in the former. By reducing the thicknesses of individual layers in the nanolaminates, bubble density and grain size were further decreased. No He bubbles were observed in the SiOC layers of the nanolaminates and the single layer SiOC film. Nanoindentation and scanning probe microscopy revealed an increase in the hardness of both single layer SiOC and Fe films after implantation. For the nanolaminates, changes in hardness were found to depend on the thicknesses of the individual layers, where reducing the layer thickness to 14 nm resulted in mitigation of implantation-induced hardening.

When simulating the response of a particle detector to an energy deposition, the pulse shape and the electronic noise are important features to be taken into account. In this work, we present a method to simulate a continuous stream of detector-like data, produced to mock the salient characteristics of the chosen setup. This technique allows the full reproduction of an experimental measurement, as well as providing a predictive tool to validate or train new analysis procedures. We present the algorithm used to produce these data, and we test its capabilities by reproducing the data output of an high-purity germanium detector.

The response of particle detectors to different types of radiation is not necessarily identical and, in some cases, neglecting this behavior can lead to a misinterpretation of the acquired data. While commercial radioactive sources are in general suitable to investigate the response to β ’s and γ ’s, in the case of α ’s the need for custom-made sources arises from the intrinsic properties of α radiation, which imposes that the emitter directly faces the detector. In this work, we show how to flexibly produce α sources to be employed in multiple studies of detector characterization. These are obtained starting from a set of primary sources obtained from the collection of radioactive 228 Ra ions at the ISOLDE facility at CERN. We illustrate the potential of this technique with practical cases of application to scintillators and bolometric detectors and examples of the results obtained so far.