Observation of a Nuclear Recoil Peak at the 100 eV Scale Induced by Neutron Capture

Coherent elastic neutrino-nucleus scattering and low-mass dark matter detectors rely crucially on the understanding of their response to nuclear recoils. We report the first observation of a nuclear recoil peak at around 112 eV induced by neutron capture. The measurement was performed with a CaWO_{4} cryogenic detector from the NUCLEUS experiment exposed to a ^{252}Cf source placed in a compact moderator. We identify the expected peak structure from the single-γ de-excitation of ^{183}W with 3σ and its origin by neutron capture with 6σ significance. This result demonstrates a new method for precise, in situ, and nonintrusive calibration of low-threshold experiments.

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.

Simulation-based design study for the passive shielding of the COSINUS dark matter experiment

The COSINUS (Cryogenic Observatory for SIgnatures seen in Next-generation Underground Searches) experiment aims at the detection of dark matter-induced recoils in sodium iodide (NaI) crystals operated as scintillating cryogenic calorimeters. The detection of both scintillation light and phonons allows performing an event-by-event signal to background discrimination, thus enhancing the sensitivity of the experiment. The choice of using NaI crystals is motivated by the goal of probing the long-standing DAMA/LIBRA results using the same target material. The construction of the experimental facility is foreseen to start by 2021 at the INFN Gran Sasso National Laboratory (LNGS) in Italy. It consists of a cryostat housing the target crystals shielded from the external radioactivity by a water tank acting, at the same time, as an active veto against cosmic ray-induced events. Taking into account both environmental radioactivity and intrinsic contamination of materials used for cryostat, shielding and infrastructure, we performed a careful background budget estimation. The goal is to evaluate the number of events that could mimic or interfere with signal detection while optimising the geometry of the experimental setup. In this paper we present the results of the detailed Monte Carlo simulations we performed, together with the final design of the setup that minimises the residual amount of background particles reaching the detector volume.

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 .

A possible role of plasma glutathione in glucose-mediated insulin secretion: in vitro and in vivo studies in rats

In isolated rat pancreatic islets exogenous glutathione which is not able to penetrate into cells, augmented glucose (11.1 mmol/l)-mediated insulin release. In the presence of a non-stimulatory glucose concentration (2.8 mmol/l) glutathione had no effect. The half-maximal synergistic action of glutathione on insulin secretion was observed at approximately 8.0 mumol/l. This concentration of glutathione is similar to that found in the plasma of non-fasted anaesthetised rats (6.5 mumol/l). Oral ingestion of glucose increased the arterial plasma glutathione in rats. Our data provide for the first time indirect evidence for a modulating effect of plasma glutathione in postprandial glucose-mediated insulin secretion which appears to be located at the extracellular site of islet cells.

Significance of gamma-glutamyl transpeptidase and thiols in amino acid uptake by rat pancreatic islets: studies with glutamine and leucine

The importance of gamma-glutamyl transpeptidase, the key enzyme of the gamma-glutamyl cycle and of thiols for the uptake of amino acids into rat pancreatic islets was investigated. Both serine-borate, an inhibitor of gamma-glutamy transpeptidase, and serine which does not inhibit this enzyme, but probably is a competitive inhibitor of amino acid uptake, inhibited the uptake of glutamine. The inhibitory effect of serine-borate was not greater than that of serine alone. The uptake of glutamine was not affected by either GSH (reduced glutathione) or diamide (a thiol oxidant). Neither substances affected the uptake of leucine. The results indicate that the uptake of glutamine by rat pancreatic islets is not dependent on the functioning of gamma-glutamyl transpeptidase and that thiols are not important for the uptake of the amino acids glutamine and leucine.