Abstract
In this article, we investigate the stability of probabilistic error cancellation (PEC) outcomes in the presence of nonstationary noise, which is an obstacle to achieving accurate observable estimates. Leveraging Bayesian methods, we design a strategy to enhance PEC stability and accuracy. Our experiments using a five-qubit implementation of the Bernstein-Vazirani algorithm and conducted on the ibm_kolkata device reveal a 42% improvement in accuracy and a 60% enhancement in stability compared to nonadaptive PEC. These results underscore the importance of adaptive estimation processes to effectively address nonstationary noise, vital for advancing PEC utility.
| Original language | English |
|---|---|
| Article number | 3102914 |
| Journal | IEEE Transactions on Quantum Engineering |
| Volume | 5 |
| DOIs | |
| State | Published - 2024 |
Funding
This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/doe-public-access-plan). This material is based upon work supported by the US Department of Energy, Office of Science, National Quantum Information Science Research Centers, Quantum Science Center.
Keywords
- Bayesian inference
- nonstationary quantum channels
- probabilistic error cancellation (PEC)
- stability