collaborators

6 papers

hep-ex2026

Overlap-aware segmentation for topological reconstruction of obscured objects

J. Schueler, H. M. Araújo, S. N. Balashov +30

The separation of overlapping objects presents a significant challenge in scientific imaging. While deep learning segmentation-regression algorithms can predict pixel-wise intensit…

hep-ex2025

Description of CRESST-III lithium aluminate data

G. Angloher, S. Banik, G. Benato +58

Two detector modules with lithium aluminate targets were operated in the CRESST underground setup between February and June 2021. The data collected in this period was used to set…

physics.ins-det2025

Description of CRESST-II and CRESST-III pulse shape data

G. Angloher, S. Banik, D. Bartolot +62

A set of data from 68 cryogenic detectors operated in the CRESST dark matter search experiment between 2013 and 2019 was collected and labeled to train binary classifiers for data…

physics.ins-det2025

Observation of a low energy nuclear recoil peak in the neutron calibration data of an AlO crystal in CRESST-III

CRESST Collaboration, G. Angloher, S. Banik +59

The current generation of cryogenic solid state detectors used in direct dark matter and CE\textnu NS searches typically reach energy thresholds of (10)eV for nucl…

astro-ph.CO2025

The CRESST experiment: towards the next-generation of sub-GeV direct dark matter detection

G. Angloher, S. Banik, A. Bento +54

Direct detection experiments have established the most stringent constraints on potential interactions between particle candidates for relic, thermal dark matter and Standard Model…

physics.ins-det2025

High-Dimensional Bayesian Likelihood Normalisation for CRESST's Background Model

G. Angloher, S. Banik, G. Benato +59

Using CaWO crystals as cryogenic calorimeters, the CRESST experiment searches for nuclear recoils caused by the scattering of potential Dark Matter particles. A reliable identi…