Kavli Affiliate: Irfan Siddiqi
| First 5 Authors: Akel Hashim, Stefan Seritan, Timothy Proctor, Kenneth Rudinger, Noah Goss
| Summary:
Contemporary methods for benchmarking noisy quantum processors typically
measure average error rates or process infidelities. However, thresholds for
fault-tolerant quantum error correction are given in terms of worst-case error
rates — defined via the diamond norm — which can differ from average error
rates by orders of magnitude. One method for resolving this discrepancy is to
randomize the physical implementation of quantum gates, using techniques like
randomized compiling (RC). In this work, we use gate set tomography to perform
precision characterization of a set of two-qubit logic gates to study RC on a
superconducting quantum processor. We find that, under RC, gate errors are
accurately described by a stochastic Pauli noise model without coherent errors,
and that spatially-correlated coherent errors and non-Markovian errors are
strongly suppressed. We further show that the average and worst-case error
rates are equal for randomly compiled gates, and measure a maximum worst-case
error of 0.0197(3) for our gate set. Our results show that randomized
benchmarks are a viable route to both verifying that a quantum processor’s
error rates are below a fault-tolerance threshold, and to bounding the failure
rates of near-term algorithms, if — and only if — gates are implemented via
randomization methods which tailor noise.
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