Improving probabilistic error cancellation in the presence of non-stationary noise

Fuente: arXiv
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Autori principali: Dasgupta, Samudra, Humble, Travis S.
Natura: Preprint
Pubblicazione: 2024
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author Dasgupta, Samudra
Humble, Travis S.
author_facet Dasgupta, Samudra
Humble, Travis S.
contents We investigate the stability of probabilistic error cancellation (PEC) outcomes in the presence of non-stationary 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 5-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 non-adaptive PEC. These results underscore the importance of adaptive estimation processes to effectively address non-stationary noise, vital for advancing PEC utility.
format Preprint
id arxiv_https___arxiv_org_abs_2404_13269
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Improving probabilistic error cancellation in the presence of non-stationary noise
Dasgupta, Samudra
Humble, Travis S.
Quantum Physics
We investigate the stability of probabilistic error cancellation (PEC) outcomes in the presence of non-stationary 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 5-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 non-adaptive PEC. These results underscore the importance of adaptive estimation processes to effectively address non-stationary noise, vital for advancing PEC utility.
title Improving probabilistic error cancellation in the presence of non-stationary noise
topic Quantum Physics
url https://arxiv.org/abs/2404.13269