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Position Reconstruction in the DEAP-3600 Dark Matter Search Experiment
Position Reconstruction in the DEAP-3600 Dark Matter Search Experiment
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Position Reconstruction in the DEAP-3600 Dark Matter Search Experiment
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Position Reconstruction in the DEAP-3600 Dark Matter Search Experiment
Position Reconstruction in the DEAP-3600 Dark Matter Search Experiment

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Position Reconstruction in the DEAP-3600 Dark Matter Search Experiment
Position Reconstruction in the DEAP-3600 Dark Matter Search Experiment
Paper

Position Reconstruction in the DEAP-3600 Dark Matter Search Experiment

B
2025
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Overview
In the DEAP-3600 dark matter search experiment, precise reconstruction of the positions of scattering events in liquid argon is key for background rejection and defining a fiducial volume that enhances dark matter candidate events identification. This paper describes three distinct position reconstruction algorithms employed by DEAP-3600, leveraging the spatial and temporal information provided by photomultipliers surrounding a spherical liquid argon vessel. Two of these methods are maximum-likelihood algorithms: the first uses the spatial distribution of detected photoelectrons, while the second incorporates timing information from the detected scintillation light. Additionally, a machine learning approach based on the pattern of photoelectron counts across the photomultipliers is explored.
Publisher
Cornell University Library, arXiv.org