Scalable deep convolutional neural networks for sparse, locally dense liquid argon time projection chamber data
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Experimental efforts searching for dark matter particles over the last few decades have ruled out many candidates led by the new generation of tonne-scale liquid xenon. For light dark matter, hydrogen could be a better target than xenon as it would offer a better kinematic match to the low mass particles. This article describes the HydroX concept, an idea to expand the dark matter sensitivity reach of large liquid xenon detectors by adding hydrogen to the liquid xenon. We discuss the nature of signal generation in liquid xenon to argue that the signal produced at the interaction site by a dark matter–hydrogen interaction could be significantly enhanced over the same interaction on xenon, increasing the sensitivity to the lightest particles. We discuss the technical implications of adding hydrogen to a xenon detector, as well as some background considerations. Finally, we make projections as to the potential sensitivity of a HydroX implementation and discuss next steps.
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