arXiv subjects

N. Hargittai

Publications and source records attributed to N. Hargittai.

3 recordsLinked to original sources

arXiv2026

HERETIX: A Hermetic, Enriched, Rare-Event Time Projection Chamber in Xenon

Xenon-based time projection chambers have established themselves as one of the most powerful technologies for rare-event searches. HERETIX is a proposed multi-tonne liquid xenon observatory featuring two nested time projection chambers that enable the simultaneous optimisation of searches for weakly interacting massive particles and neutrinoless double beta decay ($0\nu\beta\beta$) of $^{136}$Xe. A hermetically sealed sapphire vessel containing xenon enriched to 90% $^{136}$Xe forms the inner detector, providing an ultra-low-background environment for $0\nu\beta\beta$ searches. Monte Carlo studies indicate that material-induced backgrounds can be effectively eliminated, yielding a projected $0\nu\beta\beta$ half-life sensitivity of $3.2 \times 10^{28} \, \mathrm{years}$ at 90% confidence level after a 10-year exposure, while the surrounding xenon volume, depleted in $^{136}$Xe, preserves the excellent dark matter sensitivity of large liquid xenon detectors. HERETIX therefore offers a unified experimental approach capable of delivering leading sensitivity to two of the most compelling questions in fundamental physics.

physics.ins-det↗

arXiv2026

Model-independent searches of new physics in DARWIN with a semi-supervised deep learning pipeline

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-ton scale liquid Xenon-based direct detection experiment, DARWIN. We train an anomaly detector comprising a variational autoencoder and a classifier on extensive, high-dimensional simulated detector response data and construct a one-dimensional anomaly score optimised to reject the background only hypothesis in the presence of an excess of non-background-like events. We benchmark the procedure with a sensitivity study that determines its power to reject the background-only hypothesis in the presence of an injected WIMP dark matter signal, outperforming the classical, likelihood-based background rejection test. We show that our neural networks learn relevant energy features of the events from low-level, high-dimensional detector outputs, without the need to compress this data into lower-dimensional observables, thus reducing computational effort and information loss. For the future, our approach lays the foundation for an efficient end-to-end pipeline that eliminates the need for many of the corrections and cuts that are traditionally part of the analysis chain, with the potential of achieving higher accuracy and significant reduction of analysis time.

physics.ins-det↗

arXiv2023

Cosmogenic background simulations for the DARWIN observatory at different underground locations

Xenon dual-phase time projections chambers (TPCs) have proven to be a successful technology in studying physical phenomena that require low-background conditions. With 40t of liquid xenon (LXe) in the TPC baseline design, DARWIN will have a high sensitivity for the detection of particle dark matter, neutrinoless double beta decay ($0νββ$), and axion-like particles (ALPs). Although cosmic muons are a source of background that cannot be entirely eliminated, they may be greatly diminished by placing the detector deep underground. In this study, we used Monte Carlo simulations to model the cosmogenic background expected for the DARWIN observatory at four underground laboratories: Laboratori Nazionali del Gran Sasso (LNGS), Sanford Underground Research Facility (SURF), Laboratoire Souterrain de Modane (LSM) and SNOLAB. We determine the production rates of unstable xenon isotopes and tritium due to muon-included neutron fluxes and muon-induced spallation. These are expected to represent the dominant contributions to cosmogenic backgrounds and thus the most relevant for site selection.

physics.ins-det↗