Bayes-cost reduction algorithm in quantum hypothesis testing (Corresp.)

An iterative procedure is described for reducing the Bayes cost in decisions among quantum hypotheses by minimizing the average cost in binary decisions between all possible pairs of hypotheses: the resulting decision strategy is a projection-valued measure and yields an upper bound to the minimum attainable Bayes cost. From it is derived an algorithm for finding the optimum measurement states for choosing among linearly independent pure states with minimum probability of error. The method is also applied to decisions among unimodal coherent quantum signals in thermal noise.