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- W3209715250 abstract "With quantum devices for computing and simulation increasing in scale and complexity, there is a growing need for the development of tools that obtain precise diagnostic information about quantum operations. In this work, we show that by measuring random gate sequences, one can accurately and efficiently estimate a wealth of different properties of noisy implementations of gate sets. This simple experimental protocol is independent of the properties one intends to estimate. It generates `sequence shadows' from which gate-set properties can be extracted, through classical post-processing, in a state preparation and measurement error robust way. The proposed classical post-processing schemes include protocols to extract many average gate fidelities with respect to arbitrary unitary channels. This - as a special case - emulates (interleaved) randomized benchmarking, but is vastly more general in its applicability. We establish that the sequence estimation scheme can be used as a primitive for partial, compressive and full process tomography, and the learning of Pauli noise. This gives rise to channel variants of shadow estimation with close-to optimal performance guarantees. Finally, we discuss applications to the engineering cycle for the optimization of quantum gates, for instance as a novel method to diagnose crosstalk." @default.
- W3209715250 created "2021-11-08" @default.
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- W3209715250 date "2021-10-25" @default.
- W3209715250 modified "2023-09-24" @default.
- W3209715250 title "Estimating gate-set properties from random sequences" @default.
- W3209715250 hasPublicationYear "2021" @default.
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