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Efficient flexible characterization of quantum processors with nested error models

Journal Article · · New Journal of Physics

We present a simple and powerful technique for finding a good error model for a quantum processor. The technique iteratively tests a nested sequence of models against data obtained from the processor, and keeps track of the best-fit model and its wildcard error (a metric of the amount of unmodeled error) at each step. Each best-fit model, along with a quantification of its unmodeled error, constitutes a characterization of the processor. We explain how quantum processor models can be compared with experimental data and to each other. We demonstrate the technique by using it to characterize a simulated noisy two-qubit processor.

Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
Grant/Contract Number:
NA0003525
OSTI ID:
1828015
Alternate ID(s):
OSTI ID: 23180272
Report Number(s):
SAND--2021-11006J; 699163
Journal Information:
New Journal of Physics, Journal Name: New Journal of Physics Journal Issue: 9 Vol. 23; ISSN 1367-2630
Publisher:
IOP PublishingCopyright Statement
Country of Publication:
United States
Language:
English

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