activity
20232025
most citedThe XLZD Design Book: Towards the Next-Generation Liquid Xenon Observatory for Dark Matter and Neutrino Physics

21 citations · 40 across the 4 of their papers we have counts for

collaborators

5 papers

hep-ph2025★ 3 cited

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…

hep-ex2024★ 21 cited

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…

physics.ins-det2024

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…

physics.ins-det2023★ 13 cited

Magnetic microcalorimeter with paramagnetic temperature sensors and integrated dc-SQUID readout for high-resolution X-ray emission spectroscopy

Matthäus Krantz, Francesco Toschi, Benedikt Maier +3

We present two variants of a magnetic microcalorimeter with paramagnetic temperature sensors and integrated dc-SQUID readout for high-resolution X-ray emission spectroscopy. Each v…

hep-ex2023★ 3 cited

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…