Dead-time effects in photon counting distributions

Omote, Kazuhiko

doi:10.1016/0168-9002(90)90327-3

Cited by 36 publications

(42 citation statements)

References 6 publications

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“…To simplify the analysis, we normalize the symbol duration interval to [0, 1], and the dead time is normalized to τ = τ 0 /T s . The number of recorded pulses n must be less than the true number of photons N. Assuming sufficiently high sampling rate and zero noise variances of the PMT detector, the probability mass function (PMF) of detected photoelectrons number n is given by [29], summarized by the following result.…”

Section: Distribution Of Photon Counting With Dead Timementioning

confidence: 99%

“…Based on such effect, the photon counts may not satisfy a Poisson distribution. The dead time effect and the model of sub-Poisson distribution for the photon-counting processing have been investigated in [29], [30], whose variance is lower than its mean. The photon-counting system with dead time effect has been investigated in optical communication for channel characterizations [31], [32], and experimental implementation [33], [34].…”

Section: Introductionmentioning

confidence: 99%

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Characterization on Practical Photon Counting Receiver in Optical Scattering Communication

Zou

Gong

Wang

et al. 2019

IEEE Trans. Commun.

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We characterize the practical photon-counting receiver in optical scattering communication with finite sampling rate and electrical noise. In the receiver side, the detected signal can be characterized as a series of pulses generated by photon-multiplier (PMT) detector and held by the pulse-holding circuits, which are then sampled by the analog-to-digit convertor (ADC) with finite sampling rate and counted by a rising-edge pulse detector. However, the finite small pulse width incurs the dead time effect that may lead to sub-Poisson distribution on the recorded pulses. We analyze first-order and second-order moments on the number of recorded pulses with finite sampling rate at the receiver side under two cases where the sampling period is shorter than or equal to the pulse width as well as longer than the pulse width.Moreover, we adopt the maximum likelihood (ML) detection. In order to simplify the analysis, we adopt binomial distribution approximation on the number of recorded pulses in each slot. A tractable holding time and decision threshold selection rule is provided aiming to maximize the minimal Kullback-Leibler (KL) distance between the two distributions. The performance of proposed sub-Poisson distribution and the binomial approximation are verified by the experimental results. The equivalent arrival rate and holding time predicted by the of sub-Poisson model and the associated proposed binomial distribution on finite sampling rate and the electrical noise are validated by the simulation results. The proposed the holding time and decision threshold selection rule performs close to the optimal one.

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Section: Distribution Of Photon Counting With Dead Timementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characterization on Practical Photon Counting Receiver in Optical Scattering Communication

Zou

Gong

Wang

et al. 2019

IEEE Trans. Commun.

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“…Poissonian distribution needs to be modified taking the effect of td into consideration. The probability [16][17] of the incident that m pulses turn up in a period of time T0 is given by…”

Section: Setup and Theory Analysismentioning

confidence: 99%

A Bias-Free Quantum Random Number Generation Using Photon Arrival Time Selectively

et al. 2015

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We present a high-quality, bias-free quantum random number generator (QRNG) using photon arrival time selectively in accordance with the number of photon detection events within a sampling time interval in attenuated light. It is well showed in both theoretical analysis and experiments verification that this random number production method eliminates both bias and correlation perfectly without more post processing and the random number can clearly pass the standard randomness tests. We fulfill theoretical analysis and experimental verification of the method whose rate can reach up to 45Mbps.

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“…The effect becomes remarkable as the number of electrons incident on the detector increases. From the theory of dead time effects (Omote 1990), we can calculate the counting loss due to piled-up pulses (Gouhara et al 1989). For example, the counting image has the counting loss of 10% for our system when the detected current is 0.3 PA. Further analysis of the dead time effect for the counting image is a problem to be solved in the future.…”

Section: Dead Time Effectmentioning

confidence: 99%

Electron‐count imaging in SEM

et al. 1991

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We propose a method and a system for counting secondary electrons and for displaying micrographs from the SEM in real time. Evaluating the images obtained by the new system, we confirm that electron counting images have a higher signal to noise ratio than analogue images. This tendency is remarkable when the secondary electron signal is weak. We present the method and show experimental results obtained with our novel system for the detection of the secondary electron signal.

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Dead-time effects in photon counting distributions

Cited by 36 publications

References 6 publications

Characterization on Practical Photon Counting Receiver in Optical Scattering Communication

Characterization on Practical Photon Counting Receiver in Optical Scattering Communication

A Bias-Free Quantum Random Number Generation Using Photon Arrival Time Selectively

Electron‐count imaging in SEM

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