437 citations · 563 across the 15 of their papers we have counts for
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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.data-an2024★ 6 cited
XENONnT WIMP Search: Signal & Background Modeling and Statistical Inference
XENON Collaboration, E. Aprile, J. Aalbers +161
The XENONnT experiment searches for weakly-interacting massive particle (WIMP) dark matter scattering off a xenon nucleus. In particular, XENONnT uses a dual-phase time projection…
hep-ex2024
Offline tagging of radon-induced backgrounds in XENON1T and applicability to other liquid xenon detectors
E. Aprile, J. Aalbers, K. Abe +164
This paper details the first application of a software tagging algorithm to reduce radon-induced backgrounds in liquid noble element time projection chambers, such as XENON1T and X…