2021/01/31 by Christophe Piveteau, David Sutter, Stefan Woerner · 1 citation
Physics and Astronomy · #quant-ph
paper · pdf · doi:10.1038/s41534-022-00517-3
published as npj Quantum Inf, 2022 · v2: 22 pages, 9 figures; published version
arxiv created 2021/11/10 · arxiv updated 2022/02/01
Quantum error mitigation techniques can reduce noise on current quantum hardware without the need for fault-tolerant quantum error correction. For instance, the quasiprobability method simulates a noise-free quantum computer using a noisy one, with the caveat of only producing the correct expected values of observables. The cost of this error mitigation technique manifests as a sampling overhead which scales exponentially in the number of corrected gates. In this work, we present a new algorithm based on mathematical optimization that aims to choose the quasiprobability decomposition in a noise-aware manner. This directly leads to a significantly lower basis of the sampling overhead compared to existing approaches. A key element of the novel algorithm is a robust quasiprobability method that allows for a tradeoff between an approximation error and the sampling overhead via semidefinite programming.