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.

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.

Natural radionuclides as background sources in the Modane underground laboratory

The Modane underground laboratory (LSM) is the deepest operating underground laboratory in Europe. It is located under the Fréjus peak in Savoie Alps in France, with average overburden of 4800 m w. e. (water equivalent), providing low-background environment for experiments in nuclear and particle physics, astrophysics and environmental physics. It is crucial to understand individual sources of background such as residual cosmic-ray flux of high-energy muons, muon-induced neutrons and contributions from radionuclides present in the environment. The identified dominant sources of background are radioactive contamination of construction materials of detectors and laboratory walls, radon contamination of the laboratory air, and neutrons produced in the laboratory. The largest neutron contribution has been identified from (α, n) reactions in low Z materials (10^-7-10^-4 n s^-1 Bq^-1) and from spontaneous fission of ²³⁸U (1.1× 10^-6 n s^-1 Bq^-1).

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 .

Development of methods for the preparation of radiopure 82Se sources for the SuperNEMO neutrinoless double-beta decay experiment

A radiochemical method for producing 82Se sources with an ultra-low level of contamination of natural radionuclides (40K, decay products of 232Th and 238U) has been developed based on cation-exchange chromatographic purification with reverse removal of impurities. It includes chromatographic separation (purification), reduction, conditioning (which includes decantation, centrifugation, washing, grinding, and drying), and 82Se foil production. The conditioning stage, during which highly dispersed elemental selenium is obtained by the reduction of purified selenious acid (H2SeO3) with sulfur dioxide (SO2) represents the crucial step in the preparation of radiopure 82Se samples. The natural selenium (600 g) was first produced in this procedure in order to refine the method. The technique developed was then used to produce 2.5 kg of radiopure enriched selenium (82Se). The produced 82Se samples were wrapped in polyethylene (12 μm thick) and radionuclides present in the sample were analyzed with the BiPo-3 detector. The radiopurity of the plastic materials (chromatographic column material and polypropylene chemical vessels), which were used at all stages, was determined by instrumental neutron activation analysis. The radiopurity of the 82Se foils was checked by measurements with the BiPo-3 spectrometer, which confirmed the high purity of the final product. The measured contamination level for 208Tl was 8–54 μBq/kg, and for 214Bi the detection limit of 600 μBq/kg has been reached.

Environmental radionuclides as contaminants of HPGe gamma-ray spectrometers: Monte Carlo simulations for Modane underground laboratory

The main limitation in the high-sensitive HPGe gamma-ray spectrometry has been the detector background, even for detectors placed deep underground. Environmental radionuclides such as ⁴⁰K and decay products in the ²³⁸U and ²³²Th chains have been identified as the most important radioactive contaminants of construction parts of HPGe gamma-ray spectrometers. Monte Carlo simulations have shown that the massive inner and outer lead shields have been the main contributors to the HPGe-detector background, followed by aluminum cryostat, copper cold finger, detector holder and the lead ring with FET. The Monte Carlo simulated cosmic-ray background gamma-ray spectrum has been by about three orders of magnitude lower than the experimental spectrum measured in the Modane underground laboratory (4800 m w.e.), underlying the importance of using radiopure materials for the construction of ultra-low-level HPGe gamma-ray spectrometers.

Monte Carlo simulation of background characteristics of a HPGe detector operating underground in the Gran Sasso National Laboratory

Monte Carlo (MC) simulation of background components of an ultra-low background high purity germanium (HPGe) detector operating in a deep underground laboratory was carried out. The results show that the background of the HPGe detector is about two orders of magnitude higher than the MC prediction when accounting only for cosmic-ray induced background. The difference is due to natural radioactivity in the parts surrounding the Ge detector. To get reasonable agreement between MC simulations and the experiment, a contamination in the parts surrounding the Ge crystal from ⁴⁰K, ²⁰⁸Tl and ²¹⁴Bi of 0.1mBqkg^-1 was required to include in the simulations.

Simulation of background characteristics of low-level gamma-ray spectrometers using Monte Carlo method

A computing code based on the CERN's GEANT4 has been used to compute cosmic-ray background components of low-level Ge-spectrometers, optionally equipped with an anticosmic shield made of a plastic scintillation detector. The results show that the background of the Ge detector placed at 100 m w.e. (water equivalent) has decreased by a factor of 30 and 100 without and with anticosmic shielding, respectively, when compared with a surface laboratory without anticosmic shielding.