English

Improving Photoelectron Counting and Particle Identification in Scintillation Detectors with Bayesian Techniques

Instrumentation and Detectors 2015-06-22 v2 Instrumentation and Methods for Astrophysics High Energy Physics - Experiment Nuclear Experiment

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

Cite

@article{arxiv.1408.1914,
  title  = {Improving Photoelectron Counting and Particle Identification in Scintillation Detectors with Bayesian Techniques},
  author = {M. Akashi-Ronquest and P. -A. Amaudruz and M. Batygov and B. Beltran and M. Bodmer and M. G. Boulay 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 F. A. Duncan and J. A. Formaggio and R. Gagnon and D. Gastler and F. Giuliani and M. Gold and V. V. Golovko and P. Gorel and K. Graham and E. Grace and N. Guerrero and V. Guiseppe and A. L. Hallin and P. Harvey and C. Hearns and R. Henning and A. Hime and J. Hofgartner and S. Jaditz and C. J. Jillings and C. Kachulis and E. Kearns and J. Kelsey and J. R. Klein and M. Kuzniak and A. LaTorre and I. Lawson and O. Li and J. J. Lidgard and P. Liimatainen and S. Linden and K. McFarlane and D. N. McKinsey and S. MacMullin and A. Mastbaum and R. Mathew and A. B. McDonald and D. -M. Mei and J. Monroe and A. Muir and C. Nantais and K. Nicolics and J. A. Nikkel and T. Noble and E. O'Dwyer and K. Olsen and G. D. Orebi Gann and C. Ouellet and K. Palladino and P. Pasuthip and G. Perumpilly and T. Pollmann and P. Rau and F. Retiere and K. Rielage and R. Schnee and S. Seibert and P. Skensved and T. Sonley and E. Vazquez-Jauregui and L. Veloce and J. Walding and B. Wang and J. Wang and M. Ward and C. Zhang},
  journal= {arXiv preprint arXiv:1408.1914},
  year   = {2015}
}

Comments

16 pages, 16 figures

R2 v1 2026-06-22T05:23:30.776Z