4 papers
Model-independent searches of new physics in DARWIN with a semi-supervised deep learning pipeline
J. Aalbers, K. Abe, M. Adrover +231
We present a novel deep learning pipeline to perform a model-independent, likelihood-free search for anomalous (i.e., non-background) events in the proposed next generation multi-t…
The XLZD Design Book: Towards the Next-Generation Liquid Xenon Observatory for Dark Matter and Neutrino Physics
XLZD Collaboration, J. Aalbers, K. Abe +441
This report describes the experimental strategy and technologies for XLZD, the next-generation xenon observatory sensitive to dark matter and neutrino physics. In the baseline desi…
1 Particle - 1 Qubit: Particle Physics Data Encoding for Quantum Machine Learning
Aritra Bal, Markus Klute, Benedikt Maier +3
We introduce 1P1Q, a novel quantum data encoding scheme for high-energy physics (HEP), where each particle is assigned to an individual qubit, enabling direct representation of col…
Optimum filter-based analysis for the characterization of a high-resolution magnetic microcalorimeter towards the DELight experiment
Francesco Toschi, Benedikt Maier, Greta Heine +4
Ultra-sensitive cryogenic calorimeters have become a favored technology with widespread application where eV-scale energy resolutions are needed. In this article, we characterize t…