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This research investigates frustration-enhanced quantum annealing correction models that utilize additional inter-replica interactions to mitigate errors in quantum hardware. By exploiting diabatic transitions, these approaches successfully find optimal solutions for problems with small energy gaps within short annealing times, addressing a critical bottleneck for near-term devices. The findings suggest practical pathways for improving robustness against control noise and runtime limitations in current quantum annealers.
Frustration-enhanced quantum annealing correction models with additional inter-replica interactions
arXiv:2509.11217v2 Announce Type: replace-cross Abstract: Quantum annealing correction (QAC) models provide a promising approach for mitigating errors in quantum annealers. Previous studies have established that QAC models are crucial for ensuring the robustness of the ground state of the Ising model on hardware. In this work, the effects of QAC models incorporating replicas with additional interactions, specifically, the penalty spin model and the stacked model, are investigated for problems characterized by a small energy gap between the ground and first excited states during quantum annealing, a well-known bottleneck to reaching the ground state. The results demonstrate that these QAC models can obtain the optimal solution within short annealing times by exploiting diabatic transitions, even for problems with a small energy gap. These findings highlight the potential of QAC models as practical near-term algorithms for hardware subject to runtime limitations and control noise.
Abstract:Quantum annealing correction (QAC) models provide a promising approach for mitigating errors in quantum annealers. Previous studies have established that QAC models are crucial for ensuring the robustness of the ground state of the Ising model on hardware. In this work, the effects of QAC models incorporating replicas with additional interactions, specifically, the penalty spin model and the stacked model, are investigated for problems characterized by a small energy gap between the ground and first excited states during quantum annealing, a well-known bottleneck to reaching the ground state. The results demonstrate that these QAC models can obtain the optimal solution within short annealing times by exploiting diabatic transitions, even for problems with a small energy gap. These findings highlight the potential of QAC models as practical near-term algorithms for hardware subject to runtime limitations and control noise.
Statistical Mechanics (cond-mat.stat-mech); Quantum Physics (quant-ph)
arXiv:2509.11217 [cond-mat.stat-mech]
(or arXiv:2509.11217v2 [cond-mat.stat-mech] for this version)
https://doi.org/10.48550/arXiv.2509.11217 Focus to learn more arXiv-issued DOI via DataCite
Phys. Rev. A 114, 022470 (2026)
https://doi.org/10.1103/5k5x-zjq9 Focus to learn more DOI(s) linking to related resources
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