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Quantum receivers aim to effectively navigate the vast quantum-state space to endow quantum information processing capabilities unmatched by classical receivers. To date, only a handful of quantum receivers have been constructed to tackle the problem of discriminating coherent states. Quantum receivers designed by analytical approaches, however, are incapable of effectively adapting to diverse environmental conditions, resulting in their quickly diminishing performance as the operational complexities increase. Here, we present a general architecture, dubbed the quantum receiver enhanced by adaptive learning, to adapt quantum receiver structures to diverse operational conditions. The adaptively learned quantum receiver is experimentally implemented in a hardware platform with record-high efficiency. Combining the architecture and the experimental advances, the error rate is reduced up to 40% over the standard quantum limit in two coherent-state encoding schemes.

Metro and data center networks are growing rapidly, while global fixed Internet traffic growth shows evidence of slowing. An analysis of the distribution of network capacity versus distance reveals capacity gaps in networks important to wireless backhaul networks and cloud computing. These networks are built from layers of electronic aggregation switches. Photonic integration and software-defined networking control are identified as key enabling technologies for the use of optical switching in these applications. Advances in optical switching for data center and metro networks in the CIAN engineering research center are reviewed and examined as potential directions for optical communication system evolution.