arXiv:2608. 05686v1 Announce Type: cross Abstract: Quantum error correction protects logical information only when every physical operation remains below the fault-tolerance threshold, a condition that must be maintained continuously rather than only at the initial calibration.
arXiv:2607. 28422v1 Announce Type: new Abstract: Fault-tolerant quantum computing (FTQC) relies on quantum error correction to suppress physical errors and preserve logical information at scale.
The paper proposes reverse n‑wise output‑oriented testing for AI/ML and quantum computing systems, a method that builds covering arrays over output equivalence classes, confidence buckets, decision boundaries, fairness partitions, embedding clusters, ranking stability bands, quantum measurement distributions, and error syndrome patterns. It then uses gradient‑free metaheuristic optimization to solve the inverse mapping problem, generating input configurations or quantum circuit parameters that trigger specific behavioral signatures in opaque models. The framework claims to provide explicit coverage guarantees, higher fault detection rates for calibration, boundary, and error syndromes, improved test suite efficiency, and automated partition discovery for MLOps and quantum validation pipelines.
The paper investigates how an attacker could manipulate an AI adviser to issue harmful quantum error‑correction updates. It identifies an ambiguity in passive syndrome records that can mislead recovery selection and demonstrates that additional calibration measurements can provide the missing sign information needed for safe updates. By introducing a separate evaluator that only accepts updates when calibration uncertainty and drift bounds certify improvement, the authors show through simulations and surface‑code experiments that harmful proposals are rejected while beneficial ones are retained.
arXiv:2607. 19563v1 Announce Type: cross Abstract: Quantum error correction can be enhanced by post-selecting out runs that are likely to produce a logical failure, but the most accurate measures for that require costly decoder-level information.
arXiv:2607. 05814v1 Announce Type: cross Abstract: Real-time decoding is a major bottleneck in scaling quantum error correction (QEC) from noisy intermediate-scale quantum (NISQ) devices to fault-tolerant quantum computing.
The paper investigates how approximate numerical solvers used in recursive state estimation can be repaired using bounded corrections, characterizing when such corrections meet local admissibility tolerances and how they influence finite‑horizon covariance. It derives error identities that separate solve error from gain drift, revealing quartic and sixth‑order contributions to the covariance response. The framework is applied to a power‑grid tolerance study, showing that learned corrections reduce the required conjugate‑gradient iterations, and it demonstrates a unified interface for classical, quantum, and hybrid solvers.
arXiv:2606. 07666v1 Announce Type: cross Abstract: Noisy intermediate-scale quantum (NISQ) processors are entering an early fault-tolerance regime where full quantum error correction carries prohibitive resource costs, yet lightweight error detection can meaningfully improve algorithmic success rates.
arXiv:2608. 12936v1 Announce Type: cross Abstract: As quantum computing progresses from proof-of-principle demonstrations toward practical utility, a significant impediment is the need to augment algorithmic feasibility with system-level optimization across heterogeneous hardware and software stacks.
As quantum computing progresses from proof-of-principle demonstrations toward practical utility, a significant impediment is the need to augment algorithmic feasibility with system-level optimization across heterogeneous hardware and software stacks. Quantum resource estimation (QRE) plays a central role in this transition, yet existing approaches remain largely compilation-heavy or domain-knowledge-guided symbolic annotations, and tightly coupled to long-term fault-tolerant assumptions, limiting their topical applicability.
arXiv:2607. 25865v1 Announce Type: cross Abstract: Quantum error correction (QEC) is indispensable for scalable fault-tolerant quantum computing.
The paper proposes a hybrid, learning‑based strategy for selecting quantum error‑correcting codes at each concatenation level. By estimating the effective noise channel after each level, the method chooses small, non‑additive encoders when the noise has structure and switches to standard codes as the noise becomes uniform. Simulations show that this adaptive approach can achieve a target logical error rate with up to two orders of magnitude fewer qubits than using stabilizer codes alone for strongly structured noise.
arXiv:2511. 12482v2 Announce Type: replace-cross Abstract: Quantum error correction is essential for fault-tolerant quantum computing.