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Thomas point process in pulse, particle and photon detection (1983)
| Venue: | Applied Optics |
| Citations: | 4 - 3 self |
BibTeX
@ARTICLE{Matsuo83thomaspoint,
author = {Kuniaki Matsuo and Malvin Carl Teich and Bahaa E. A. Saleh},
title = {Thomas point process in pulse, particle and photon detection},
journal = {Applied Optics},
year = {1983},
volume = {22},
pages = {1898--1909}
}
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Abstract
Multiplication effects in point processes are important in a number of areas of electrical engineering and physics. We examine the properties and applications of a point process that arises when each event of a primary Poisson process generates a random number of subsidiary events with a given time course. The multiplication factor is assumed to obey the Poisson probability law, and the dynamics of the time delay are associated with a linear filter of arbitrary impulse response function; special attention is devoted to the rectangular and exponential case. Primary events are included in the final point process, which is expected to have applications in pulse, particle, and photon detection. We refer to this as the Thomas point process since the counting distribution reduces to the Thomas distribution in the limit of long counting times. Explicit results are obtained for the singlefold and multifold counting statistics (distribution of the number of events registered in a fixed counting time), the time statistics (forward recurrence time and interevent probability densities), and the counting correlation function (noise properties). These statistics can provide substantial insight into the underlying physical mechanisms generating the process. An example of the applicability of the model is provided by betaluminescence photons produced in a glass photomultiplier tube, when Cherenkov events are also present. I.
Keyphrases
thomas point process photon detection point process time delay special attention multifold counting statistic multiplication effect counting distribution reduces fixed counting time noise property thomas distribution linear filter subsidiary event recurrence time primary poisson process exponential case counting correlation function multiplication factor cherenkov event random number final point process time statistic interevent probability density substantial insight long counting time glass photomultiplier tube explicit result time course arbitrary impulse response function underlying physical mechanism electrical engineering primary event betaluminescence photon poisson probability law
