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In-situ characterization of quantum devices with error correction
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Syndrome measurements made in quantum error correction contain more information than is typically used. We show that the statistics of data from syndrome measurements can be used to do the following: (i) estimation of parameters of an error channel, including the ability correct away the invertible part of the error channel, once it is estimated; (ii) hypothesis testing (or model selection) to distinguish error channels, e.g., to determine if the errors are correlated. The unifying theme is to make use of all of the information in the statistics of the data collected from syndrome measurements using machine learning and control algorithms.
Forward citations
Cited by 2 Pith papers
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Exponential logical-error reduction in quantum memories via optimal syndrome-measurement timing
The optimal syndrome-measurement interval scales inversely with code distance and yields exponential logical-error reduction for surface-code quantum memories.
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Simulating Quantum State Transfer between Distributed Devices using Noisy Interconnects
A noisy quantum channel can simulate a perfect state transfer via a quasiprobability recipe whose sampling overhead is 2/F - 1, where F is the channel's entanglement fidelity, validated on IBM quantum hardware.
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