Quantum strategy stores isometry channels with n = Θ(1/√ε) queries for error ε, quadratic improvement over classical n = Θ(ε^{-1}).
Quantum learning algorithms for quantum measurements
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abstract
We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples. The analysis of the case of three examples reveals that, differently from the learning of unitary gates, the optimal algorithm for learning of quantum measurements cannot be parallelized, and requires quantum memories for the storage of information.
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quant-ph 1years
2025 1verdicts
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Quantum Advantage in Storage and Retrieval of Isometry Channels
Quantum strategy stores isometry channels with n = Θ(1/√ε) queries for error ε, quadratic improvement over classical n = Θ(ε^{-1}).