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Adaptive folding and noise filtering for robust quantum error mitigation

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arxiv 2505.04463 v1 pith:TVLKHUKJ submitted 2025-05-07 quant-ph

classification quant-ph
keywords adaptiveerrorfilteringnoiseextrapolationquantumscalingfactors
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum Noise Mitigation with Adaptive Zero-Noise Extrapolation: A Contextual Multi-Armed Bandits Approach

    quant-ph 2026-08 conditional novelty 6.0 of 10

    A contextual bandit that adaptively selects ZNE folding levels reduces quantum circuit execution round trips by up to 40% and exchanged bytes by 35% while slightly improving estimator fidelity in simulated VQC training.

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