Characterizing the Reproducibility of Noisy Quantum Circuits

Dasgupta, Samudra; Humble, Travis S.

doi:10.3390/e24020244

Characterizing the Reproducibility of Noisy Quantum Circuits

Journal Article · Sat Feb 05 00:00:00 EST 2022 · Entropy

DOI:https://doi.org/10.3390/e24020244· OSTI ID:1864425

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Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Quantum Science Center; Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center for Interdisciplinary Research and Graduate Education

The ability of a quantum computer to reproduce or replicate the results of a quantum circuit is a key concern for verifying and validating applications of quantum computing. Statistical variations in circuit outcomes that arise from ill-characterized fluctuations in device noise may lead to computational errors and irreproducible results. While device characterization offers a direct assessment of noise, an outstanding concern is how such metrics bound the reproducibility of a given quantum circuit. Here, we first directly assess the reproducibility of a noisy quantum circuit, in terms of the Hellinger distance between the computational results, and then we show that device characterization offers an analytic bound on the observed variability. We validate the method using an ensemble of single qubit test circuits, executed on a superconducting transmon processor with well-characterized readout and gate error rates. The resulting description for circuit reproducibility, in terms of a composite device parameter, is confirmed to define an upper bound on the observed Hellinger distance, across the variable test circuits. This predictive correlation between circuit outcomes and device characterization offers an efficient method for assessing the reproducibility of noisy quantum circuits.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1864425

Journal Information:: Entropy, Journal Name: Entropy Journal Issue: 2 Vol. 24; ISSN 1099-4300

Publisher:: MDPICopyright Statement

Country of Publication:: United States

Language:: English

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Snowmass White Paper: Quantum Computing Systems and Software for High-energy Physics Research Humble, Travis S.; Delgado, Andrea; Pooser, Raphael arXiv https://doi.org/10.48550/arxiv.2203.07091	preprint	January 2022

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