To learn and cancel quantum noise: Probabilistic error cancellation with sparse Pauli-Lindblad models on noisy quantum processors

Speaker: Zlatko Minev, IBM

Date: Jan 26, 2023 10:00 am

Location: PSC 2136 (Speaker will be at UMD in-person)
https://umd.zoom.us/j/5942646305

Abstract:

Error-mitigation techniques can enable access to accurate estimates of physical observables that are otherwise biased by noise in pre-fault-tolerant quantum computers. One particularly general error-mitigation technique is probabilistic error cancellation (PEC), which effectively inverts a well-characterized noise channel to produce noise-free estimates of observables. Experimental realizations of this technique, however, have been impeded by the challenge of learning correlated noise in large quantum circuits. In this work, we present a practical protocol for learning a sparse noise model that scales to large quantum devices and is efficient to learn and invert. These advances enable us to demonstrate PEC on a superconducting quantum processor with crosstalk errors, thereby revealing a path to error-mitigated quantum computation with noise-free observables at larger circuit volumes.