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Khosa, C. K., Mars, L., Richards, J., & Sanz, V. (2020). Convolutional neural networks for direct detection of dark matter. J. Phys. G, 47(9), 095201–20pp.
Abstract: The XENON1T experiment uses a time projection chamber (TPC) with liquid xenon to search for weakly interacting massive particles (WIMPs), a proposed dark matter particle, via direct detection. As this experiment relies on capturing rare events, the focus is on achieving a high recall of WIMP events. Hence the ability to distinguish between WIMP and the background is extremely important. To accomplish this, we suggest using convolutional neural networks (CNNs); a machine learning procedure mainly used in image recognition tasks. To explore this technique we use XENON collaboration open-source software to simulate the TPC graphical output of dark matter signals and main backgrounds. A CNN turns out to be a suitable tool for this purpose, as it can identify features in the images that differentiate the two types of events without the need to manipulate or remove data in order to focus on a particular region of the detector. We find that the CNN can distinguish between the dominant background events (ER) and 500 GeV WIMP events with a recall of 93.4%, precision of 81.2% and an accuracy of 87.2%.
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Loya Villalpando, A. A., Martin-Albo, J., Chen, W. T., Guenette, R., Lego, C., Park, J. S., et al. (2020). Improving the light collection efficiency of silicon photomultipliers through the use of metalenses. J. Instrum., 15(11), P11021–13pp.
Abstract: Metalenses are optical devices that implement nanostructures as phase shifters to focus incident light. Their compactness and simple fabrication make them a potential cost-effective solution for increasing light collection efficiency in particle detectors with limited photosensitive area coverage. Here we report on the characterization and performance of metalenses in increasing the light collection efficiency of silicon photomultipliers (SiPM) of various sizes using an LED of 630 nm, and find a six to seven-fold increase in signal for a 1.3 x 1 3 mm(2) SiPM when coupled with a 10-mm-diameter metalens manufactured using deep ultraviolet stepper lithography. Such improvements could be valuable for future generations of particle detectors, particularly those employed in rare-event searches such as dark matter and neutrinoless double beta decay.
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Rebel, B., Hall, C., Bernard, E., Faham, C. H., Ito, T. M., Lundberg, B., et al. (2014). High voltage in noble liquids for high energy physics. J. Instrum., 9, T08004–57pp.
Abstract: A workshop was held at Fermilab November 8-9, 2013 to discuss the challenges of using high voltage in noble liquids. The participants spanned the fields of neutrino, dark matter, and electric dipole moment physics. All presentations at the workshop were made in plenary sessions. This document summarizes the experiences and lessons learned from experiments in these fields at developing high voltage systems in noble liquids.
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XENON Collaboration(Aprile, E. et al), & Orrigo, S. E. A. (2014). Conceptual design and simulation of a water Cherenkov muon veto for the XENON1T experiment. J. Instrum., 9, P11006–20pp.
Abstract: XENON is a dark matter direct detection project, consisting of a time projection chamber (TPC) filled with liquid xenon as detection medium. The construction of the next generation detector, XENON1T, is presently taking place at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy. It aims at a sensitivity to spin-independent cross sections of 2.10(47) cm(2) for WIMP masses around 50 GeV/c(2), which requires a background reduction by two orders of magnitude compared to XENON100, the current generation detector. An active system that is able to tag muons and muon-induced backgrounds is critical for this goal. A water Cherenkov detector of similar to 10m height and diameter has been therefore developed, equipped with 8 inch photomultipliers and cladded by a reflective foil. We present the design and optimization study for this detector, which has been carried out with a series of Monte Carlo simulations. The muon veto will reach very high detection efficiencies for muons (> 99.5%) and showers of secondary particles from muon interactions in the rock (> 70%). Similar efficiencies will be obtained for XENONnT, the upgrade of XENON1T, which will later improve the WIMP sensitivity by another order of magnitude. With the Cherenkov water shield studied here, the background from muon-induced neutrons in XENON1T is negligible.
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