Statistical method for resolving the photonphotoelectron-counting inversion problem
A statistical inversion method is proposed for the photonphotoelectron-counting statistics in quantum key distribution experiment. With the statistical viewpoint, this problem is equivalent to the parameter estimation for an infinite binomial mixture model. The coarse-graining idea and Bayesian methods are applied to deal with this ill-posed problem, which is a good simple example to show the successful application of the statistical methods to the inverse problem. Numerical results show the applicability of the proposed strategy. The coarse-graining idea for the infinite mixture models should be general to be used in the future.
quantum key distribution infinite binomial mixture model coarse-graining bayesian methods ill-posed problem photon statistics