Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques

M. Akashi-Ronquest; P. A. Amaudruz; M. Batygov; B. Beltran; M. Bodmer; M. G. Boulay; B. Broerman; B. Buck; A. Butcher; B. Cai; T. Caldwell; M. Chen; Y. Chen; B. Cleveland; K. Coakley; K. Dering; F. A. Duncan; J. A. Formaggio; R. Gagnon; D. Gastler; F. Giuliani; M. Gold; V. V. Golovko; P. Gorel; K. Graham; E. Grace; N. Guerrero; V. Guiseppe; A. L. Hallin; P. Harvey; C. Hearns; R. Henning; A. Hime; J. Hofgartner; S. Jaditz; C. J. Jillings; C. Kachulis; E. Kearns; J. Kelsey; J. R. Klein; M. Kuźniak; A. Latorre; I. Lawson; O. Li; J. J. Lidgard; P. Liimatainen; S. Linden; K. McFarlane; D. N. McKinsey; S. Macmullin; A. Mastbaum; R. Mathew; A. B. McDonald; D. M. Mei; J. Monroe; A. Muir; C. Nantais; K. Nicolics; J. A. Nikkel; T. Noble; E. O'Dwyer; K. Olsen; G. D. Orebi Gann; C. Ouellet; K. Palladino; P. Pasuthip; G. Perumpilly; T. Pollmann; P. Rau; F. Retière; K. Rielage; R. Schnee; S. Seibert; P. Skensved; T. Sonley; E. Vázquez-Jáuregui; L. Veloce; J. Walding; B. Wang; J. Wang; M. Ward; C. Zhang

doi:10.1016/j.astropartphys.2014.12.006

Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques

M. Akashi-Ronquest, P. A. Amaudruz, M. Batygov, B. Beltran, M. Bodmer, M. G. Boulay, B. Broerman, B. Buck, A. Butcher, B. Cai, T. Caldwell, M. Chen, Y. Chen, B. Cleveland, K. Coakley, K. Dering, F. A. Duncan, J. A. Formaggio, R. Gagnon, D. GastlerF. Giuliani, M. Gold, V. V. Golovko, P. Gorel, K. Graham, E. Grace, N. Guerrero, V. Guiseppe, A. L. Hallin, P. Harvey, C. Hearns, R. Henning, A. Hime, J. Hofgartner, S. Jaditz, C. J. Jillings, C. Kachulis, E. Kearns, J. Kelsey, J. R. Klein, M. Kuźniak, A. Latorre, I. Lawson, O. Li, J. J. Lidgard, P. Liimatainen, S. Linden, K. McFarlane, D. N. McKinsey, S. Macmullin, A. Mastbaum, R. Mathew, A. B. McDonald, D. M. Mei, J. Monroe, A. Muir, C. Nantais, K. Nicolics, J. A. Nikkel, T. Noble, E. O'Dwyer, K. Olsen, G. D. Orebi Gann, C. Ouellet, K. Palladino, P. Pasuthip, G. Perumpilly, T. Pollmann, P. Rau, F. Retière, K. Rielage, R. Schnee, S. Seibert, P. Skensved, T. Sonley, E. Vázquez-Jáuregui, L. Veloce, J. Walding, B. Wang, J. Wang, M. Ward, C. Zhang

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	40-54
Number of pages	15
Journal	Astroparticle Physics
Volume	65
DOIs	https://doi.org/10.1016/j.astropartphys.2014.12.006
State	Published - May 2015
Externally published	Yes

Funding

Support for DEAP-1 has been provided by the Canadian Foundation for Innovation and the Natural Sciences and Engineering Research Council . The High Performance Computing Virtual Laboratory (HPCVL) has provided us with CPU time, data storage, and support. We would also like to thank the SNOLAB staff for on-site support. The work of our co-op and summer students, including Christopher Stanford who operated DEAP-1 during the data-taking in this paper, is gratefully acknowledged. This work has in part been supported by the United States Department of Energy , Office of High Energy Physics .

Funders	Funder number
U.S. Department of Energy
High Energy Physics
Natural Sciences and Engineering Research Council of Canada
Canada Foundation for Innovation
Science and Technology Facilities Council	ST/K502261/1, ST/K001264/1, ST/K002570/1

Keywords

Dark matter
Liquid argon
Neutrino
Pulse-shape discrimination

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10.1016/j.astropartphys.2014.12.006

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Akashi-Ronquest, M., Amaudruz, P. A., Batygov, M., Beltran, B., Bodmer, M., Boulay, M. G., Broerman, B., Buck, B., Butcher, A., Cai, B., Caldwell, T., Chen, M., Chen, Y., Cleveland, B., Coakley, K., Dering, K., Duncan, F. A., Formaggio, J. A., Gagnon, R., ... Zhang, C. (2015). Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques. Astroparticle Physics, 65, 40-54. https://doi.org/10.1016/j.astropartphys.2014.12.006

@article{853478779bdc4b50855aff10292be2d4,

title = "Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques",

abstract = "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.",

keywords = "Dark matter, Liquid argon, Neutrino, Pulse-shape discrimination",

author = "M. Akashi-Ronquest and Amaudruz, {P. A.} and M. Batygov and B. Beltran and M. Bodmer and Boulay, {M. G.} and B. Broerman and B. Buck and A. Butcher and B. Cai and T. Caldwell and M. Chen and Y. Chen and B. Cleveland and K. Coakley and K. Dering and Duncan, {F. A.} and Formaggio, {J. A.} and R. Gagnon and D. Gastler and F. Giuliani and M. Gold and Golovko, {V. V.} and P. Gorel and K. Graham and E. Grace and N. Guerrero and V. Guiseppe and Hallin, {A. L.} and P. Harvey and C. Hearns and R. Henning and A. Hime and J. Hofgartner and S. Jaditz and Jillings, {C. J.} and C. Kachulis and E. Kearns and J. Kelsey and Klein, {J. R.} and M. Ku{\'z}niak and A. Latorre and I. Lawson and O. Li and Lidgard, {J. J.} and P. Liimatainen and S. Linden and K. McFarlane and McKinsey, {D. N.} and S. Macmullin and A. Mastbaum and R. Mathew and McDonald, {A. B.} and Mei, {D. M.} and J. Monroe and A. Muir and C. Nantais and K. Nicolics and Nikkel, {J. A.} and T. Noble and E. O'Dwyer and K. Olsen and {Orebi Gann}, {G. D.} and C. Ouellet and K. Palladino and P. Pasuthip and G. Perumpilly and T. Pollmann and P. Rau and F. Reti{\`e}re and K. Rielage and R. Schnee and S. Seibert and P. Skensved and T. Sonley and E. V{\'a}zquez-J{\'a}uregui and L. Veloce and J. Walding and B. Wang and J. Wang and M. Ward and C. Zhang",

year = "2015",

month = may,

doi = "10.1016/j.astropartphys.2014.12.006",

language = "English",

volume = "65",

pages = "40--54",

journal = "Astroparticle Physics",

issn = "0927-6505",

publisher = "Elsevier",

}

Akashi-Ronquest, M, Amaudruz, PA, Batygov, M, Beltran, B, Bodmer, M, Boulay, MG, Broerman, B, Buck, B, Butcher, A, Cai, B, Caldwell, T, Chen, M, Chen, Y, Cleveland, B, Coakley, K, Dering, K, Duncan, FA, Formaggio, JA, Gagnon, R, Gastler, D, Giuliani, F, Gold, M, Golovko, VV, Gorel, P, Graham, K, Grace, E, Guerrero, N, Guiseppe, V, Hallin, AL, Harvey, P, Hearns, C, Henning, R, Hime, A, Hofgartner, J, Jaditz, S, Jillings, CJ, Kachulis, C, Kearns, E, Kelsey, J, Klein, JR, Kuźniak, M, Latorre, A, Lawson, I, Li, O, Lidgard, JJ, Liimatainen, P, Linden, S, McFarlane, K, McKinsey, DN, Macmullin, S, Mastbaum, A, Mathew, R, McDonald, AB, Mei, DM, Monroe, J, Muir, A, Nantais, C, Nicolics, K, Nikkel, JA, Noble, T, O'Dwyer, E, Olsen, K, Orebi Gann, GD, Ouellet, C, Palladino, K, Pasuthip, P, Perumpilly, G, Pollmann, T, Rau, P, Retière, F, Rielage, K, Schnee, R, Seibert, S, Skensved, P, Sonley, T, Vázquez-Jáuregui, E, Veloce, L, Walding, J, Wang, B, Wang, J, Ward, M & Zhang, C 2015, 'Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques', Astroparticle Physics, vol. 65, pp. 40-54. https://doi.org/10.1016/j.astropartphys.2014.12.006

TY - JOUR

T1 - Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques

AU - Akashi-Ronquest, M.

AU - Amaudruz, P. A.

AU - Batygov, M.

AU - Beltran, B.

AU - Bodmer, M.

AU - Boulay, M. G.

AU - Broerman, B.

AU - Buck, B.

AU - Butcher, A.

AU - Cai, B.

AU - Caldwell, T.

AU - Chen, M.

AU - Chen, Y.

AU - Cleveland, B.

AU - Coakley, K.

AU - Dering, K.

AU - Duncan, F. A.

AU - Formaggio, J. A.

AU - Gagnon, R.

AU - Gastler, D.

AU - Giuliani, F.

AU - Gold, M.

AU - Golovko, V. V.

AU - Gorel, P.

AU - Graham, K.

AU - Grace, E.

AU - Guerrero, N.

AU - Guiseppe, V.

AU - Hallin, A. L.

AU - Harvey, P.

AU - Hearns, C.

AU - Henning, R.

AU - Hime, A.

AU - Hofgartner, J.

AU - Jaditz, S.

AU - Jillings, C. J.

AU - Kachulis, C.

AU - Kearns, E.

AU - Kelsey, J.

AU - Klein, J. R.

AU - Kuźniak, M.

AU - Latorre, A.

AU - Lawson, I.

AU - Li, O.

AU - Lidgard, J. J.

AU - Liimatainen, P.

AU - Linden, S.

AU - McFarlane, K.

AU - McKinsey, D. N.

AU - Macmullin, S.

AU - Mastbaum, A.

AU - Mathew, R.

AU - McDonald, A. B.

AU - Mei, D. M.

AU - Monroe, J.

AU - Muir, A.

AU - Nantais, C.

AU - Nicolics, K.

AU - Nikkel, J. A.

AU - Noble, T.

AU - O'Dwyer, E.

AU - Olsen, K.

AU - Orebi Gann, G. D.

AU - Ouellet, C.

AU - Palladino, K.

AU - Pasuthip, P.

AU - Perumpilly, G.

AU - Pollmann, T.

AU - Rau, P.

AU - Retière, F.

AU - Rielage, K.

AU - Schnee, R.

AU - Seibert, S.

AU - Skensved, P.

AU - Sonley, T.

AU - Vázquez-Jáuregui, E.

AU - Veloce, L.

AU - Walding, J.

AU - Wang, B.

AU - Wang, J.

AU - Ward, M.

AU - Zhang, C.

PY - 2015/5

Y1 - 2015/5

N2 - 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.

AB - 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.

KW - Dark matter

KW - Liquid argon

KW - Neutrino

KW - Pulse-shape discrimination

UR - http://www.scopus.com/inward/record.url?scp=84919934363&partnerID=8YFLogxK

U2 - 10.1016/j.astropartphys.2014.12.006

DO - 10.1016/j.astropartphys.2014.12.006

M3 - Article

AN - SCOPUS:84919934363

SN - 0927-6505

VL - 65

SP - 40

EP - 54

JO - Astroparticle Physics

JF - Astroparticle Physics

ER -

Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques

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Keywords

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