Dataset Information

Detecting and tracking drift in quantum information processors.

ABSTRACT: If quantum information processors are to fulfill their potential, the diverse errors that affect them must be understood and suppressed. But errors typically fluctuate over time, and the most widely used tools for characterizing them assume static error modes and rates. This mismatch can cause unheralded failures, misidentified error modes, and wasted experimental effort. Here, we demonstrate a spectral analysis technique for resolving time dependence in quantum processors. Our method is fast, simple, and statistically sound. It can be applied to time-series data from any quantum processor experiment. We use data from simulations and trapped-ion qubit experiments to show how our method can resolve time dependence when applied to popular characterization protocols, including randomized benchmarking, gate set tomography, and Ramsey spectroscopy. In the experiments, we detect instability and localize its source, implement drift control techniques to compensate for this instability, and then demonstrate that the instability has been suppressed.

SUBMITTER: Proctor T

PROVIDER: S-EPMC7588494 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Detecting and tracking drift in quantum information processors.

Proctor Timothy T Revelle Melissa M Nielsen Erik E Rudinger Kenneth K Lobser Daniel D Maunz Peter P Blume-Kohout Robin R Young Kevin K

Nature communications 20201026 1

If quantum information processors are to fulfill their potential, the diverse errors that affect them must be understood and suppressed. But errors typically fluctuate over time, and the most widely used tools for characterizing them assume static error modes and rates. This mismatch can cause unheralded failures, misidentified error modes, and wasted experimental effort. Here, we demonstrate a spectral analysis technique for resolving time dependence in quantum processors. Our method is fast, s ...[more]

PMID: 33106482

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Dataset Information

Detecting and tracking drift in quantum information processors.

Publications

Detecting and tracking drift in quantum information processors.

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