Journal article icon

Journal article

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.

Actions

Access Document

Publisher copy:
10.1016/j.astropartphys.2014.12.006

Authors


Publisher:
Elsevier
Journal:
Astroparticle Physics More from this journal
Volume:
65
Pages:
40-54
Publication date:
2014-08-08
DOI:
ISSN:
0927-6505


Language:
English
Keywords:
Pubs id:
pubs:480063
UUID:
uuid:ec965ed6-4b60-4f86-b9b9-e95bed844ccc
Local pid:
pubs:480063
Source identifiers:
480063
Deposit date:
2014-08-17
ARK identifier:

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP