Enhanced Extrapolation-Based Quantum Error Mitigation Using Repetitive Structure in Quantum Algorithms
Boseon Kim, Wooyeong Song, Kwangil Bae, Wonhyuk Lee, IlKwon Sohn

TL;DR
This paper introduces a novel error mitigation framework for structured quantum algorithms with repetitive blocks, improving accuracy over traditional zero-noise extrapolation, especially under high noise conditions.
Contribution
The paper proposes a lightweight, extrapolation-based error mitigation method that characterizes errors of repeated operational blocks, enhancing robustness in noisy quantum computations.
Findings
Achieves over 20% higher success probability than ZNE in high-noise scenarios.
Demonstrates exponential decay of core block errors in simulations.
Approaches theoretical success probability in low-noise conditions.
Abstract
Quantum error mitigation is a crucial technique for suppressing errors especially in noisy intermediate-scale quantum devices, enabling more reliable quantum computation without the overhead of full error correction. Zero-Noise Extrapolation (ZNE), which we mainly consider in this work, is one of prominent quantum error mitigation methods. For algorithms with deep circuits - such as iterative quantum algorithms involving multiple oracle calls - ZNE's effectiveness is significantly degraded under high noise. Extrapolation based on such low-fidelity data often yields inaccurate estimates and requires substantial overhead. In this study, we propose a lightweight, extrapolation-based error mitigation framework tailored for structured quantum algorithms composed of repeating operational blocks. The proposed method characterizes the error of the repeated core operational block, rather than…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography
