Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning.

Cryogenic phonon detectors with transition-edge sensors achieve the best sensitivity to sub-GeV/c dark matter interactions with nuclei in current direct detection experiments. In such devices, the temperature of the thermometer and the bias current in its readout circuit need careful optimization to achieve optimal detector performance. This task is not trivial and is typically done manually by an expert.

Contributions of fossil and non-fossil fractions to total carbon in urban aerosols in Bratislava (Slovakia).

Radiocarbon measurements of total carbon (TC) fraction of aerosol samples collected at the campus of the Comenius University in Bratislava (Slovakia) during 2022-2023 were carried out. Based on radiocarbon activity of these samples and a source apportionment model we have determined the relative proportion of fossil and non-fossil carbon in collected atmospheric aerosols. The carbon from non-fossil sources (biomass burning and biogenic emissions) was dominant in this time period, on average it formed 72% of carbon present in the aerosols from the atmosphere of Bratislava.

Long-term radiocarbon variation studies in the air and tree rings of Slovakia.

Fifty-five years of radiocarbon variation studies are reviewed with an emphasis on a better understanding of the impacts of the Bohunice nuclear power plant and fossil fuel CO on the atmosphere and biosphere of Slovakia. The maximum ΔC levels in the air up to about 1200‰ were observed during the 1970s at the Žlkovce monitoring station, which after 2005 decreased to <30‰. A relative decrease in the atmospheric ΔC levels due to increasing levels of fossil CO in the atmosphere has also been significant, for example, in Bratislava down to about -330‰, but after 2005 they were only <50‰ below the Jungfraujoch European clean-air level.

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.

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

CRESST is a leading direct detection sub-GeVc dark matter experiment. During its second phase, cryogenic bolometers were used to detect nuclear recoils off the CaWO target crystal nuclei. The previously established electromagnetic background model relies on Secular Equilibrium (SE) assumptions.