Reinforcement-learning calibration of coherent-state receivers on variable-loss optical channels

We study the problem of calibrating a quantum receiver for optical coherent states when transmitted on a quantum optical channel with variable transmissivity, a common model for long-distance optical-fiber and free/deep-space optical communication [1]–[7]. We optimize the error probability of legacy adaptive receivers, such as Kennedy’s and Dolinar’s [8], [9], on average with respect to the channe...