Loss of antibunching

Abstract

We describe some of the main external mechanisms that lead to a loss of antibunching, i.e., that spoil the character of a given quantum light to deliver its photons separated from each other. Namely, we consider contamination by noise, a time jitter in the photon detection, and the effect of frequency filtering (or detection with finite bandwidth). The formalism to describe time jitter is derived and connected to the already existing one for frequency filtering. The emission from a two-level system under both incoherent and coherent driving is taken as a particular case of special interest. The coherent case is further separated into its vanishing-(Heitler) and high-(Mollow) driving regimes. We provide analytical solutions which, in the case of filtering, reveal an unsuspected structure in the transitions from perfect antibunching to thermal (incoherent case) or uncorrelated (coherent case) emission. The experimental observations of these basic and fundamental transitions would provide additional compelling evidence of the correctness and importance of the theory of frequency-resolved photon correlations.

Tuning photon statistics with coherent fields

“…For two-photon suppression, this results in photons correlations of the type of Eqs. ( 2) and ( 3) to be much more resilient to time-frequency uncertainties and, correspondingly, to provide much better antibunching and less "accidental" coincidences, due to the flatter short-time correlation τ 2 [19]. In Ref.…”

“…One is that the quest for perfect single-photon sources has been so far driven by technological improvements to reduce g (2) (0) as much as possible from the basic structure of a two-level system. This is a quantitative and asymptotic race that is doomed to imperfection as the limitations are fundamental: photodetection as a physical process will always detect simultaneous photons from a two-level system [19]. To obtain perfect single-photon emission, one must open a gap somewhere [16].…”

Parameter estimation from quantum-jump data using neural networks

“…In the particular case of photon-counting with single-photon detectors, numerous sources of noise can be attributed just to the detection process, such as the efficiency, bandwidth, dead time, dark counts or jitter noise [71]. All these sources of noise have non-trivial consequences on the statistics of the photodetection events [88] and on the quantum trajectories associated to these imperfect measurements [89]. Hence, the necessity of a perfect modelling and characterization of these processes seriously hampers the utilization of Bayesian inference.…”

“…We illustrate the potential advantage brought in by the estimation with NNs by considering the particular case of time jitter [88], which we describe by adding a noise term to the values of time delays τ used both in the training and estimation of the NNs for the 1D estimation case θ = [∆]. We consider noise following a normal distribution with standard deviation σ τ , so that x → x + x noise (σ τ ), with x noise (σ τ ) ∼ N (0, σ τ ).…”