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This study demonstrates how noise-informed decoding and component exclusion strategies can significantly improve logical error rates on monolithic superconducting processors with inherent fabrication heterogeneity. By dynamically adapting measurement schedules and leveraging lattice surgery, the researchers achieved high-fidelity fault-tolerant logic even when excluding underperforming qubits and couplers. These results provide a critical roadmap for scaling superconducting quantum computers by mitigating hardware imperfections without requiring perfect uniformity across the chip.
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Error-Corrected Memory and Logic on a Heavy-Hex Superconducting-Qubit Processor

arXiv3 min read

arXiv:2610.11658v1 Announce Type: new Abstract: Large quantum computations require high-fidelity error-corrected memory and fault-tolerant logical operations. To achieve these with superconducting circuits, quantum processors will need many components operating with low error rates. In practice, fabrication of monolithic superconducting devices produces unavoidable heterogeneity in component performance, which the quantum computer must accommodate. We implement strategies to operate a large dynamic compass code on an array of 156 superconducting qubits arranged on a heavy-hexagonal lattice, making use of the entire monolithic quantum processor and redesigning our measurement schedule to exclude underperforming components. We demonstrate improvements of up to $35\%$ in logical error probabilities for a memory experiment by using a noise-informed decoder combined with strategies to exclude the worst-performing qubits and couplers, along with post-selecting on shots with a low probability of leakage errors. In addition to these memory results, we also observe performance gains of up to $56\%$ when these strategies are applied to measurement-based logic, demonstrated by stability experiments. We furthermore demonstrate high-fidelity fault-tolerant logic through lattice surgery. Through pre-selection filtering techniques, we can obtain Bell fidelities above $77\%$, and further logical gap post-selection using exclusive decoding increases these fidelities to above $97\%$. Our experiments demonstrate that high performance can be maintained in key elements of fault-tolerant quantum memory and logic when working on monolithic superconducting quantum processors with underperforming components, by using a suite of noise-informed quantum error correction strategies.

Abstract:Large quantum computations require high-fidelity error-corrected memory and fault-tolerant logical operations. To achieve these with superconducting circuits, quantum processors will need many components operating with low error rates. In practice, fabrication of monolithic superconducting devices produces unavoidable heterogeneity in component performance, which the quantum computer must accommodate. We implement strategies to operate a large dynamic compass code on an array of 156 superconducting qubits arranged on a heavy-hexagonal lattice, making use of the entire monolithic quantum processor and redesigning our measurement schedule to exclude underperforming components. We demonstrate improvements of up to $35\%$ in logical error probabilities for a memory experiment by using a noise-informed decoder combined with strategies to exclude the worst-performing qubits and couplers, along with post-selecting on shots with a low probability of leakage errors. In addition to these memory results, we also observe performance gains of up to $56\%$ when these strategies are applied to measurement-based logic, demonstrated by stability experiments. We furthermore demonstrate high-fidelity fault-tolerant logic through lattice surgery. Through pre-selection filtering techniques, we can obtain Bell fidelities above $77\%$, and further logical gap post-selection using exclusive decoding increases these fidelities to above $97\%$. Our experiments demonstrate that high performance can be maintained in key elements of fault-tolerant quantum memory and logic when working on monolithic superconducting quantum processors with underperforming components, by using a suite of noise-informed quantum error correction strategies.

arXiv:2610.11658 [quant-ph]

(or arXiv:2610.11658v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2610.11658 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 318 words

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