  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.
