Abstract:Measurement-based realtime control is an important strategy in quantum information processing, which is applied in fields from qubit readout to error corrections. However, the time cost of quantum measurement inevitably induces a latency in the control process and limits its performance. Here we introduce the deep learning approach to relax this restriction by predicting and compensating the latency-induced control error. We experimentally implement feedforward quantum control of a single-spin system of nitrog… Show more
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