Dark matter implications from the XENONnT and LZ data
Haipeng An, Fei Gao, Jia Liu, Minghao Liu, Haoming Nie, Changlong Xu

TL;DR
This study explores dark matter explanations for high-energy recoil events in XENONnT and LZ data, using a unified framework to fit multiple datasets and considering velocity-dependent and inelastic interactions, with implications for future high-energy analyses.
Contribution
First combined profile-likelihood analysis of XENONnT and LZ data addressing high-energy recoil events with novel dark matter interaction models.
Findings
Velocity-dependent and inelastic dark matter interactions can explain high-energy recoil spectrum.
Significance of dark matter interpretation varies from below 1σ to 4σ depending on background assumptions.
Future high-energy data will be crucial for testing the dark matter hypothesis.
Abstract
We investigate a possible dark matter origin of the high-energy nuclear-recoil-like events in XENONnT and LZ data, which cannot be explained by standard elastic spin-independent WIMP scattering. Using our unified DIAMX framework, built on openly available data and likelihood models, we perform the first combined profile-likelihood fits to multiple WIMP-search datasets with a total exposure of 7.3 tonneyear. We investigate that two broad classes of dark matter nucleon interactions, with velocity-dependent cross-section or inelastic (endo- and exothermic) scattering, can reproduce the observed high-energy recoil spectrum, reaching local significances up to . We further quantify the impact of Xe double electron capture (DEC) backgrounds, finding that variations in the poorly known DEC charge yields can shift the inferred significances from below to…
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Taxonomy
TopicsDark Matter and Cosmic Phenomena · Particle physics theoretical and experimental studies · Computational Physics and Python Applications
