Modeling noisy quantum circuits using experimental characterization

Noisy intermediate-scale quantum (NISQ) devices offer unique platforms to test and evaluate the behavior of computing. However, validating circuits on NISQ is difficult due fluctuations in underlying noise sources other nonreproducible behaviors that generate computational errors. Here we present a test-driven approach decomposes noisy, application-specific circuit into series bootstrapped experiments device. By characterizing individual subcircuits, composite model for original circuit. We demonstrate this applications Greenberger-Horne-Zeilinger(GHZ)-state preparation Bernstein-Vazirani algorithm family superconducting transmon devices. measure accuracy using total variation distance between predicted experimental results, works well across multiple instances. Our shown be computationally efficient offers trade-off complexity can tailored desired predictive accuracy.