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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Online Testing Error Mitigation for Quantum Computers

Cheng-Yun Hsieh, James Chien-Mo Li

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.1109/tcad.2026.3705986

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Near-term quantum processors operate in the noisy intermediate-scale quantum (NISQ) region, where it is impractical to implement fault-tolerant error correction. Quantum Error Mitigation (QEM) provides a practical alternative, but most existing approaches rely on computationally intensive classical resources which are impractical to implement in embedded or edge-controlled systems. This work presents an adaptive, hardware-aware QEM framework designed for resource-constrained classical processors, demonstrated using a Raspberry Pi 5 as an edge controller for IBM Quantum hardware. A deep neural network predicts circuit fidelity and entropy from circuit and hardware features, enabling an online fuzzy-logic policy selector to choose among no mitigation, dynamical decoupling, and zero-noise extrapolation. Using real hardware feedback, an adaptive bias mechanism update policy was developed. The system operates without full-state simulation or offline recalibration and is evaluated on both randomized and benchmark-referenced circuits. Results show stable mitigation behaviour across depth regimes, primarily preventing fidelity degradation and selectively improving output similarity where mitigation is effective. This work demonstrates the feasibility of adaptive QEM deployment on classical edge devices under strict resource constraints.
We apply quantum error mitigation techniques to a variety of benchmark problems and quantum computers to evaluate the performance of quantum error mitigation in practice. To do so, we define an empirically motivated, resource-normalized metric of the improvement of error mitigation which we call the improvement factor, and calculate this metric for each experiment we perform. The experiments we perform consist of zero-noise extrapolation and probabilistic error cancellation applied to two benchmark problems run on IBM, IonQ, and Rigetti quantum computers, as well as noisy quantum computer simulators. Our results show that error mitigation is on average more beneficial than no error mitigation — even when normalized by the additional resources used — but also emphasize that the performance of quantum error mitigation depends on the underlying computer.