Measurement of the 2νßß Decay Half-Life of

We report on the results obtained with the global CUPID-0 background model, which combines the data collected in the two measurement campaigns for a total exposure of 8.82 kg×yr of ^{82}Se. We identify with improved precision the background sources within the 3 MeV energy region, where neutrinoless double ß decay of ^{82}Se and ^{100}Mo is expected, making more solid the foundations for the background budget of the next-generation CUPID experiment. Relying on the excellent data reconstruction, we measure the two-neutrino double ß-decay half-life of ^{82}Se with unprecedented accuracy: T_{1/2}^{2ν}=[8.69±0.05(stat)_{-0.06}^{+0.09}(syst)]×10^{19} yr.

Characterization of a kg-scale archaeological lead-based PbWO4 cryogenic detector for the RES-NOVA experiment.

Core-collapse Supernovae (SNe) are one of the most energetic events in the Universe, during which almost all the star's binding energy is released in the form of neutrinos. These particles are direct probes of the processes occurring in the stellar core and provide unique insights into the gravitational collapse. RES-NOVA will revolutionize how we detect neutrinos from astrophysical sources, by deploying the first ton-scale array of cryogenic detectors made from archaeological lead. Pb offers the highest neutrino interaction cross-section via coherent elastic neutrino-nucleus scattering (CEνNS). Such process will enable RES-NOVA to be equally sensitive to all neutrino flavours. For the first time, we propose the use archaeological Pb as sensitive target material in order to achieve an ultra-low background level in the region of interest (O(1 keV)). All these features make possible the deployment of the first cm-scale neutrino telescope for the investigation of astrophysical sources. In this contribution, we will characterize the radiopurity level and the performance of a small-scale proof-of-principle detector of RES-NOVA, consisting in a PbWO4 crystal made from archaeological-Pb operated as cryogenic detector.

Towards an automated data cleaning with deep learning in CRESST.

The CRESST experiment employs cryogenic calorimeters for the sensitive measurement of nuclear recoils induced by dark matter particles. The recorded signals need to undergo a careful cleaning process to avoid wrongly reconstructed recoil energies caused by pile-up and read-out artefacts. We frame this process as a time series classification task and propose to automate it with neural networks. With a data set of over one million labeled records from 68 detectors, recorded between 2013 and 2019 by CRESST, we test the capability of four commonly used neural network architectures to learn the data cleaning task. Our best performing model achieves a balanced accuracy of 0.932 on our test set. We show on an exemplary detector that about half of the wrongly predicted events are in fact wrongly labeled events, and a large share of the remaining ones have a context-dependent ground truth. We furthermore evaluate the recall and selectivity of our classifiers with simulated data. The results confirm that the trained classifiers are well suited for the data cleaning task.

Secular equilibrium assessment in a CaWO4 target crystal from the dark matter experiment CRESST using Bayesian likelihood normalisation.

CRESST is a leading direct detection sub-GeVc-2 dark matter experiment. During its second phase, cryogenic bolometers were used to detect nuclear recoils off the CaWO4 target crystal nuclei. The previously established electromagnetic background model relies on Secular Equilibrium (SE) assumptions. In this work, a validation of SE is attempted by comparing two likelihood-based normalisation results using a recently developed spectral template normalisation method based on Bayesian likelihood. Albeit we find deviations from SE in some cases we conclude that these deviations are artefacts of the fit and that the assumptions of SE is physically meaningful.

Erratum: Measurement of the 2νßß Decay Half-Life of

This corrects the article DOI: 10.1103/PhysRevLett.126.171801.

New Direct Limit on Neutrinoless Double Beta Decay Half-Life of

The Cryogenic Underground Observatory for Rare Events (CUORE) at Laboratori Nazionali del Gran Sasso of INFN in Italy is an experiment searching for neutrinoless double beta (0νßß) decay. Its main goal is to investigate this decay in ^{130}Te, but its ton-scale mass and low background make CUORE sensitive to other rare processes as well. In this Letter, we present our first results on the search for 0νßß decay of ^{128}Te, the Te isotope with the second highest natural isotopic abundance. We find no evidence for this decay, and using a Bayesian analysis we set a lower limit on the ^{128}Te 0νßß decay half-life of T_{1/2}>3.6×10^{24} yr (90% CI). This represents the most stringent limit on the half-life of this isotope, improving by over a factor of 30 the previous direct search results, and exceeding those from geochemical experiments for the first time.

Final Result on the Neutrinoless Double Beta Decay of

CUPID-0, an array of Zn^{82}Se cryogenic calorimeters, was the first medium-scale demonstrator of the scintillating bolometers' technology. The first project phase (March 2017-December 2018) allowed the most stringent limit on the neutrinoless double beta decay half-life of the isotope of interest, ^{82}Se, to be set. After a six month long detector upgrade, CUPID-0 began its second and last phase (June 2019-February 2020). In this Letter, we describe the search for neutrinoless double beta decay of ^{82}Se with a total exposure (phase I+II) of 8.82 kg yr^{-1} of isotope. We set a limit on the half-life of ^{82}Se to the ground state of ^{82}Kr of T_{1/2}^{0ν}(^{82}Se)>4.6×10^{24} yr (90% credible interval), corresponding to an effective Majorana neutrino mass m_{ßß}<(263-545) meV. We also set the most stringent lower limits on the neutrinoless decays of ^{82}Se to the 0_{1}^{+}, 2_{1}^{+}, and 2_{2}^{+} excited states of ^{82}Kr, finding 1.8×10^{23} yr, 3.0×10^{23} yr, and 3.2×10^{23} yr (90% credible interval) respectively.

Background identification in cryogenic calorimeters through α - α delayed coincidences.

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 232 Th and 238 U 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.

Measurement of the 2νßß Decay Half-Life of

We measured two-neutrino double beta decay of ^{130}Te using an exposure of 300.7 kg yr accumulated with the CUORE detector. Using a Bayesian analysis to fit simulated spectra to experimental data, it was possible to disentangle all the major background sources and precisely measure the two-neutrino contribution. The half-life is in agreement with past measurements with a strongly reduced uncertainty: T_{1/2}^{2ν}=7.71_{-0.06}^{+0.08}(stat)_{-0.15}^{+0.12}(syst)×10^{20} yr. This measurement is the most precise determination of the ^{130}Te 2νßß decay half-life to date.

Improved Limit on Neutrinoless Double-Beta Decay in

We report new results from the search for neutrinoless double-beta decay in ^{130} Te with the CUORE detector. This search benefits from a fourfold increase in exposure, lower trigger thresholds, and analysis improvements relative to our previous results. We observe a background of (1.38±0.07)×10^{-2} counts/(keV kg yr)) in the 0νßß decay region of interest and, with a total exposure of 372.5 kg yr, we attain a median exclusion sensitivity of 1.7×10^{25} yr. We find no evidence for 0νßß decay and set a 90% credibility interval Bayesian lower limit of 3.2×10^{25} yr on the ^{130} Te half-life for this process. In the hypothesis that 0νßß decay is mediated by light Majorana neutrinos, this results in an upper limit on the effective Majorana mass of 75-350 meV, depending on the nuclear matrix elements used.

Geant4-based electromagnetic background model for the CRESST dark matter experiment.

The CRESST (Cryogenic Rare Event Search with Superconducting Thermometers) dark matter search experiment aims for the detection of dark matter particles via elastic scattering off nuclei in CaWO 4 crystals. To understand the CRESST electromagnetic background due to the bulk contamination in the employed materials, a model based on Monte Carlo simulations was developed using the Geant4 simulation toolkit. The results of the simulation are applied to the TUM40 detector module of CRESST-II phase 2. We are able to explain up to ( 68 ± 16 ) % of the electromagnetic background in the energy range between 1 and 40 keV .

Coupling multitemporal remote sensing with geomorphology and hydrological modeling for post flood recovery in the Strymonas dammed river basin (Greece).

We present a case study of a long-term integrated monitoring of a flood event which affected part of the Strymonas dammed river basin, a transboundary river with source in Bulgaria, which flows then through Greece to the Aegean Sea. The event, which affected the floodplain downstream the Kerkini dam, started at the beginning of April 2015, due to heavy rain upstream of the monitored area, and lasted for several months, with some water pools still present at the beginning of September, due to the peculiar geomorphological conditions of the watershed. We collected a multi-temporal dataset consisting of a high-resolution, X-band COSMO-SkyMed, and several C-band Sentinel-1 SAR and optical Landsat-8 images of the area. The results allow following the event in time, sketching a multi-temporal map of the post-flood evolution, with relatively high temporal resolution. We then use hydrological modeling to mimic the dynamics of the flooded area against post event weather patterns and thus explain the observed flood extent evolution. We show how integrating remote sensing-derived maps of flooded areas, geomorphological analyses of the landscape and simplified hydrological modeling allows accurate inference about long-term dynamics of flooded areas, very important in the post event in anthropogenic highly modified areas, where recovery time after the flood event is considerable, and long term water persistence may lead to large consequences, carrying economic damages and medical emergencies.

First Result on the Neutrinoless Double-ß Decay of

We report the result of the search for neutrinoless double beta decay of ^{82}Se obtained with CUPID-0, the first large array of scintillating Zn^{82}Se cryogenic calorimeters implementing particle identification. We observe no signal in a 1.83 kg yr ^{82}Se exposure, and we set the most stringent lower limit on the 0νßß ^{82}Se half-life T_{1/2}^{0ν}>2.4×10^{24} yr (90% credible interval), which corresponds to an effective Majorana neutrino mass m_{ßß}<(376-770) meV depending on the nuclear matrix element calculations. The heat-light readout provides a powerful tool for the rejection of α particles and allows us to suppress the background in the region of interest down to (3.6_{-1.4}^{+1.9})×10^{-3} counts/(keV kg yr), an unprecedented level for this technique.

Search of the neutrino-less double beta decay of 82 Se into the excited states of 82 Kr with CUPID-0.

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 · yr (2.24 × 10 25  emitters · yr). We found no evidence of the decays and set the most stringent limits on the widths of these processes: Γ ( 82 Se → 82 Kr 0 1 + )8.55 × 10 - 24  yr - 1 , Γ ( 82 Se → 82 Kr 2 1 + ) < 6.25 × 10 - 24  yr - 1 , Γ ( 82 Se → 82 Kr 2 2 + )8.25 × 10 - 24  yr - 1 (90 % credible interval).

Analysis of cryogenic calorimeters with light and heat read-out for double beta decay searches.

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 α 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 α 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.

CUPID-0: the first array of enriched scintillating bolometers for 0 ν ß ß decay investigations.

The CUPID-0 detector hosted at the Laboratori Nazionali del Gran Sasso, Italy, is the first large array of enriched scintillating cryogenic detectors for the investigation of 82 Se neutrinoless double-beta decay ( 0 ν ß ß ). CUPID-0 aims at measuring a background index in the region of interest (RoI) for 0 ν ß ß at the level of 10 - 3  counts/(keV kg years), the lowest value ever measured using cryogenic detectors. CUPID-0 operates an array of Zn 82 Se scintillating bolometers coupled with bolometric light detectors, with a state of the art technology for background suppression and thorough protocols and procedures for the detector preparation and construction. In this paper, the different phases of the detector design and construction will be presented, from the material selection (for the absorber production) to the new and innovative detector structure. The successful construction of the detector lead to promising preliminary detector performance which is discussed here.

First array of enriched Zn[Formula: see text]Se bolometers to search for double beta decay.

The R&D activity performed during the last years proved the potential of ZnSe scintillating bolometers to the search for neutrino-less double beta decay, motivating the realization of the first large-mass experiment based on this technology: CUPID-0. The isotopic enrichment in [Formula: see text]Se, the Zn[Formula: see text]Se crystals growth, as well as the light detectors production have been accomplished, and the experiment is now in construction at Laboratori Nazionali del Gran Sasso (Italy). In this paper we present the results obtained testing the first three Zn[Formula: see text]Se crystals operated as scintillating bolometers, and we prove that their performance in terms of energy resolution, background rejection capability and intrinsic radio-purity complies with the requirements of CUPID-0.

CALDER: neutrinoless double-beta decay identification in TeO[Formula: see text] bolometers with kinetic inductance detectors.

Next-generation experiments searching for neutrinoless double-beta decay must be sensitive to a Majorana neutrino mass as low as 10[Formula: see text]. CUORE , an array of 988 TeO[Formula: see text] bolometers being commissioned at Laboratori Nazionali del Gran Sasso, features an expected sensitivity of 50-130[Formula: see text] at 90 % C.L. The background is expected to be dominated by [Formula: see text] radioactivity, and can be in principle removed by detecting the small amount of Cherenkov  light emitted by the [Formula: see text] signal. The Cryogenic wide-Area Light Detectors with Excellent Resolution project aims at developing a small prototype experiment consisting of TeO[Formula: see text] bolometers coupled to high-sensitivity light detectors based on kinetic inductance detectors. The R&D is focused on the light detectors in view of the implementation in a next-generation neutrinoless double-beta decay experiment.

Regularized least squares classifiers may predict Crohn's disease from profiles of single nucleotide polymorphisms.

In this paper we focus on the prediction of Crohn's disease (CD) susceptibility by analyzing SNP profiles for a number of defined or suggested gene polymorphisms. We assess the correlation between genetic markers and the phenotype by using well-founded methods and procedures developed in the field of statistical learning theory. To this end, we use a sample generated by a case-control study composed of 178 CD patients and 127 healthy controls. The genetic profile of each subject is composed of 16 genetic variants distributed over 11 genes. We find that regularized least squares (RLS) classifiers predict Crohn's disease with a statistically significant accuracy of 62%(p= 0.018), significantly increasing the diagnostic accuracy by at least 10% compared to that obtained with the more largely confirmed gene involved in CD predisposition, namely CARD15. This also demonstrates that our sample size is adequate for accurate and significant prediction estimates. The strength of this methodology, in contrast to classical statistical methods, is that it accounts simultaneously for the effect of several genetics markers and their possible interactions. The findings of this study show that RLS methodology is able to increase the diagnostic accuracy of CD prediction by contemporary evaluation of a large number of gene polymorphisms. This approach may be particularly useful in large-scale population screening programs, and when evaluating large datasets of gene polymorphisms (i.e. chips, microarrays). Moreover, it could shed more light on possible candidate genes with a weak genetic contribution, and for evaluating gene-gene and gene-phenotype interactions by analyzing populations with a reasonably small sample size.

On the statistical assessment of classifiers using DNA microarray data.

BACKGROUND: In this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia--Italy. The data set is made up of normal (22) and tumor (25) specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data. RESULTS: We estimate the generalization error, evaluated through the Leave-K-Out Cross Validation error, for three different classification schemes by varying the number of training examples and the number of the genes used. The statistical significance of the error rate is measured by using a permutation test. We provide a statistical analysis in terms of the frequencies of the genes involved in the classification. Using the whole set of genes, we found that the Weighted Voting Algorithm (WVA) classifier learns the distinction between normal and tumor specimens with 25 training examples, providing e = 21% (p = 0.045) as an error rate. This remains constant even when the number of examples increases. Moreover, Regularized Least Squares (RLS) and Support Vector Machines (SVM) classifiers can learn with only 15 training examples, with an error rate of e = 19% (p = 0.035) and e = 18% (p = 0.037) respectively. Moreover, the error rate decreases as the training set size increases, reaching its best performances with 35 training examples. In this case, RLS and SVM have error rates of e = 14% (p = 0.027) and e = 11% (p = 0.019). Concerning the number of genes, we found about 6000 genes (p < 0.05) correlated with the pathology, resulting from the signal-to-noise statistic. Moreover the performances of RLS and SVM classifiers do not change when 74% of genes is used. They progressively reduce up to e = 16% (p < 0.05) when only 2 genes are employed. The biological relevance of a set of genes determined by our statistical analysis and the major roles they play in colorectal tumorigenesis is discussed. CONCLUSIONS: The method proposed provides statistically significant answers to precise questions relevant for the diagnosis and prognosis of cancer. We found that, with as few as 15 examples, it is possible to train statistically significant classifiers for colon cancer diagnosis. As for the definition of the number of genes sufficient for a reliable classification of colon cancer, our results suggest that it depends on the accuracy required.