Adaptive folding and noise filtering for robust quantum error mitigation

TL;DR

This paper introduces adaptive noise-aware techniques for quantum error mitigation, combining adaptive folding and filtering methods to improve the accuracy of zero-noise extrapolation in noisy quantum computations.

Contribution

It proposes noise-adaptive folding with error-based scaling and two filtering methods, enhancing zero-noise extrapolation's robustness against noise fluctuations.

Findings

Adaptive scaling improves extrapolation accuracy.

Filtering methods enhance error mitigation.

Significant reduction in expectation-value errors.

Abstract

Coping with noise in quantum computation poses significant challenges due to its unpredictable nature and the complexities of accurate modeling. This paper presents noise-adaptive folding, a technique that enhances zero-noise extrapolation (ZNE) through the use of adaptive scaling factors based on circuit error measurements. Furthermore, we introduce two filtering methods: one relies on measuring error strength, while the other utilizes statistical filtering to improve the extrapolation process. Comparing our approach with standard ZNE reveals that adaptive scaling factors can be optimized using either a noise model or direct error strength measurements from inverted circuits. The integration of adaptive scaling with filtering techniques leads to notable improvements in expectation-value extrapolation over standard ZNE. Our findings demonstrate that these adaptive methods effectively strengthen error mitigation against noise fluctuations, thereby enhancing the precision and reliability of quantum computations.