Hans Kraus

Abstract:

Recently low-mass dark matter direct searches have been hindered by a low-energy background, drastically reducing the physics reach of the experiments. In the CRESST-III experiment, this signal is characterised by a significant increase of events below 200 eV. As the origin of this background is still unknown, it became necessary to develop new detector designs to reach a better understanding of the observations. Within the CRESST collaboration, three new different detector layouts have been developed, and they are presented in this contribution.

Abstract:

Diamond operated as a cryogenic calorimeter is an excellent target for direct detection of low-mass dark matter candidates. Following the realization of the first low-threshold cryogenic detector that uses diamond as absorber for astroparticle physics applications, we now present the resulting exclusion limits on the elastic spin-independent interaction cross-section of dark matter with diamond. We measured two 0.175 g CVD (Chemical Vapor Deposition) diamond samples, each instrumented with a Transition Edge Sensor made of Tungsten (W-TES). Thanks to the energy threshold of just 16.8 eV of one of the two detectors, we set exclusion limits on the elastic spin-independent interaction of dark matter particles with carbon nuclei down to dark matter masses as low as 0.122 GeV/c2. This work shows the scientific potential of cryogenic detectors made from diamond and lays the foundation for the use of this material as target for direct detection dark matter experiments.

Abstract:

The Cryogenic Rare Event Search with Superconducting Thermometers (CRESST) experiment employs scintillating crystals at extremely low temperatures (O(10 mK)) to search for nuclear recoils from hypothetical dark matter (DM) particles. CRESST has achieved thresholds below 100 eV with a wide range of target materials including CaWO4, LiAlO2, Al2O3, and Si. However, at these energies, the ability to discriminate between potential DM signals and electromagnetic background is insufficient. A detailed Geant4-based electromagnetic background model was developed for CRESST and is being continuously adapted to CRESST's current inventory of detector modules. We use a high-dimensional Bayesian likelihood fit of spectral templates to the measured spectrum to infer activities of various background sources. A template for the calibration source used to calculate the energy scale will be included in the likelihood fit. We present the status of CRESST's background model, and results from the simulation of the energy calibration. Our future plans of improving the background model are also discussed.