Various random point processes occurring in the detection of photons in different states are considered. Statistics of the times between these points and their correlation are analysed.
We consider the situation in which the field of quantum particles such as photons (bosons) or electrons (fermions) undergoes a significant attenuation during the detection process. We characterize the second-order statistical properties of the field by the bunching for bosons and the antibunching for fermions. Bunching and antibunching effects are derived from the time intervals distributions of the random point process of detection instead of the moments of the number of particles registered in a given time interval. Fields of both beams are supposed to be in chaotic states and have second-order time correlation functions of exponential profile and of arbitrary correlation time. A test is proposed for nonclassical states: the behavior of the antibunching function is a nondecreasing function near the origin of the time axis.
This paper is concerned with the study of statistical properties of various optical fields obtained by several types of laser intensity modulation from the stationary random point process point of view. We essentially consider intensity correlations and time intervals distributions (TID). A generalization of the already known TID is given: It is the probability distribution (MTID) of the time interval between one photoelectron and the n th following photoelectron. Some theoretical and experimental results are presented in the general case (the time intervals considered are not necessarily small compared to the coherence time of the field). The modulation effect can be characterized by the photoelectron bunching effect. The TID and the MTID are significantly dependent upon the spectral profile of the field, if the used time scale is of the order of the coherence time. On the other hand, the MTID can be interpreted as the probability of the sum over time intervals between two successive photoelectrons. We treat two cases: If the variables of this sum are uncorrelated, we verify the central-limit theorem; if the variables are correlated we study the influence of the correlations when the number of summed variables becomes large.