Title: Quantum Error Mitigation via Adaptive Bias Correction

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum computing holds immense promise for complex computations far exceeding the capabilities of classical computers. However, current quantum hardware suffers from inherent errors, which can severely limit the performance of these systems. Quantum error mitigation (QEM) techniques aim to detect and correct these errors, but they often require significant calibration and can be computationally demanding. This paper proposes a novel quantum error mitigation strategy employing an adaptive bias correction mechanism. Our approach dynamically adjusts bias correction parameters based on the observed error rate, minimizing the impact of errors on computation while maintaining high accuracy. We introduce a 'adaptive bias profile' algorithm that continuously monitors error patterns and optimizes correction strength to achieve optimal error reduction. This innovative strategy offers a more robust and adaptable approach to QEM, potentially reducing the need for extensive calibration and improving overall system performance. The results demonstrate the effectiveness of our method in mitigating errors across a range of quantum algorithms, showcasing its potential to significantly enhance the practical usability of quantum computation.

DOI: 10.5281/zenodo.22255169

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