Model Refinement of Noisy Quantum Circuits Using Experimental Characterization

Current quantum processing units represent noisy intermediate scale quantum systems that tend to be poorly characterized. Accurate modeling of these devices can provide insight into the underlying noise as well as methods for mitigating errors. We present a test-driven methodology for quantifying QPU performance and characterizing NISQ behavior that offers an alternative to costly experimental characterizations using standard tomographic methods. We demonstrate modeling of noisy gate operations by fitting experimental characterization circuits using a series of bootstrapped numerical methods. We generate parameterized gate models that are composed easily to model noisy quantum circuits. We demonstrate the effectiveness of this modeling method for applications of GHZ state preparation and the Bernstein-Vazirani algorithm using a family of superconducting transmon QPUs. We quantify the accuracy of the generated models using the total variation distance between experimental observations and numerically simulated results. Our results show that model refinement from test-driven experimental characterization offers an accessible methodology for approximating performance of NISQ devices.