Photon Flux and Bunching Noise from Measurement of the Shot Noise Variance

Abstract

We report the experimental observation of photon bunching noise through shot noise measurements made on a pseudo-thermal state of light using balanced detection. A full theory describing the measurement is developed, and in agreement with theory it is found that the shot noise variance in the balanced signal reproduces the time series of the flux of the primary incoherent beam. Moreover, when the average power of the pseudo-thermal light is varied, the balanced detection is seen to track this change. A comparison of direct detection and balanced detection of the thermal field, shows that the balanced detection performs at least as well the direct detection and under some conditions appears to outperform the direct detection. There is not necessarily a contradiction with quantum field theory which predicts that at best the performance of the balanced detection should be equal to the direct detection, because the direct detection process is subject to nonlinearity that has not been excluded by measurements (even though any tests we performed suggest such effects are small). This is the first time that the bunching noise effect of high occupation number chaotic light via the shot noise of the field has successfully been measured, to the point of using it to infer the flux of the field. The findings may be relevant to radio receiver design, specifically from the viewpoint of sensitivity improvement.

Convolutional neural network‐based model observer for signal known statistically task in breast tomosynthesis images

“…electronic noise was generated following a Poisson distribution with a variance of 209 electrons (i.e., $$5238 \times 2 \times 2 \times O(10^{-2})$$); charge collection coefficient (i.e., conversion rate of optical photons to e‐h pairs by the photodiode) of 1 was used during this implementation. To reduce the effect of electronic noise, the mean value of the added electronic noise was calibrated to zero 44–48 . The Hanning‐weighted ramp filter was then applied to the projection data 49 .…”

“…To reduce the effect of electronic noise, the mean value of the added electronic noise was calibrated to zero. [44][45][46][47][48] The Hanning-weighted ramp filter was then applied to the projection data. 49 The filtered projection data were voxel-driven backprojected with linear interpolation to reconstruct a breast tomosynthesis volume of size 64×64×16 (i.e., 6.4×6.4×6.4 mm 3 ).Note that the reconstructed voxel size was 0.1×0.1×0.4 mm 3 in our work, thus resulting in a slice thickness of 0.4 mm.…”