Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques
Many current and future dark matter and neutrino detectors are designed to measure scintillation light with a large array of photomultiplier tubes (PMTs). The energy resolution and particle identification capabilities of these detectors depend in part on the ability to accurately identify individual...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | en_US |
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Elsevier
2017
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| Online Access: | http://hdl.handle.net/1721.1/108648 https://orcid.org/0000-0002-3757-9883 |
| _version_ | 1826208936708014080 |
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| author | Buck, Benjamin R. Formaggio, Joseph A Jaditz, Stephen Hunter Kelsey, James E |
| author2 | Lincoln Laboratory |
| author_facet | Lincoln Laboratory Buck, Benjamin R. Formaggio, Joseph A Jaditz, Stephen Hunter Kelsey, James E |
| author_sort | Buck, Benjamin R. |
| collection | MIT |
| description | Many current and future dark matter and neutrino detectors are designed to measure scintillation light with a large array of photomultiplier tubes (PMTs). The energy resolution and particle identification capabilities of these detectors depend in part on the ability to accurately identify individual photoelectrons in PMT waveforms despite large variability in pulse amplitudes and pulse pileup. We describe a Bayesian technique that can identify the times of individual photoelectrons in a sampled PMT waveform without deconvolution, even when pileup is present. To demonstrate the technique, we apply it to the general problem of particle identification in single-phase liquid argon dark matter detectors. Using the output of the Bayesian photoelectron counting algorithm described in this paper, we construct several test statistics for rejection of backgrounds for dark matter searches in argon. Compared to simpler methods based on either observed charge or peak finding, the photoelectron counting technique improves both energy resolution and particle identification of low energy events in calibration data from the DEAP-1 detector and simulation of the larger MiniCLEAN dark matter detector. |
| first_indexed | 2024-09-23T14:14:40Z |
| format | Article |
| id | mit-1721.1/108648 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T14:14:40Z |
| publishDate | 2017 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | mit-1721.1/1086482022-10-01T20:05:28Z Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques Buck, Benjamin R. Formaggio, Joseph A Jaditz, Stephen Hunter Kelsey, James E Lincoln Laboratory Massachusetts Institute of Technology. Department of Physics Buck, Benjamin R. Formaggio, Joseph A Jaditz, Stephen Hunter Kelsey, James E Many current and future dark matter and neutrino detectors are designed to measure scintillation light with a large array of photomultiplier tubes (PMTs). The energy resolution and particle identification capabilities of these detectors depend in part on the ability to accurately identify individual photoelectrons in PMT waveforms despite large variability in pulse amplitudes and pulse pileup. We describe a Bayesian technique that can identify the times of individual photoelectrons in a sampled PMT waveform without deconvolution, even when pileup is present. To demonstrate the technique, we apply it to the general problem of particle identification in single-phase liquid argon dark matter detectors. Using the output of the Bayesian photoelectron counting algorithm described in this paper, we construct several test statistics for rejection of backgrounds for dark matter searches in argon. Compared to simpler methods based on either observed charge or peak finding, the photoelectron counting technique improves both energy resolution and particle identification of low energy events in calibration data from the DEAP-1 detector and simulation of the larger MiniCLEAN dark matter detector. 2017-05-03T19:42:56Z 2017-05-03T19:42:56Z 2014-12 2014-11 Article http://purl.org/eprint/type/JournalArticle 0927-6505 http://hdl.handle.net/1721.1/108648 Akashi-Ronquest, M.; Amaudruz, P.-A.; Batygov, M.; Beltran, B.; Bodmer, M.; Boulay, M.G.; Broerman, B. et al. “Improving Photoelectron Counting and Particle Identification in Scintillation Detectors with Bayesian Techniques.” Astroparticle Physics 65 (May 2015): 40–54. © 2014 Elsevier B.V. https://orcid.org/0000-0002-3757-9883 en_US http://dx.doi.org/10.1016/j.astropartphys.2014.12.006 Astroparticle Physics Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier arXiv |
| spellingShingle | Buck, Benjamin R. Formaggio, Joseph A Jaditz, Stephen Hunter Kelsey, James E Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques |
| title | Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques |
| title_full | Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques |
| title_fullStr | Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques |
| title_full_unstemmed | Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques |
| title_short | Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques |
| title_sort | improving photoelectron counting and particle identification in scintillation detectors with bayesian techniques |
| url | http://hdl.handle.net/1721.1/108648 https://orcid.org/0000-0002-3757-9883 |
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