arXiv:2601. 00242v2 Announce Type: replace-cross Abstract: Realizing the full potential of quantum computation requires Quantum Error Correction (QEC).
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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.
arXiv:2608. 15760v1 Announce Type: cross Abstract: Decoding is an essential component of quantum error correction (QEC), translating stabilizer measurement outcomes into corrective actions that suppress logical errors and preserve logical quantum information.
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 introduces QuBA, a Quantum Bayesian graph Attention decoder that provides expressive error-pattern recognition and calibrated uncertainty estimates for quantum error correction. It also presents SAGU, a multi-phase training framework that enhances cross-domain robustness, allowing decoding beyond the training set. Experiments on bivariate bicycle codes show that both QuBA and SAGU outperform classical belief propagation, achieving up to two orders of magnitude lower logical error rates and comparable or better performance than domain-specific training approaches.
arXiv:2503.24111v4 Announce Type: replace-cross Abstract: Graph Neural Networks (QGNNs) offer a promising approach to combining quantum computing with graph-structured data processing. While classica...
The paper introduces a new objective function for designing quantum error correction codes that maximizes the distinguishability of quantum states after a noise channel. This approach, called variational quantum error correction (VarQEC), uses a distinguishability loss function as a machine learning objective to discover encoding circuits tailored to specific noise characteristics. The authors demonstrate that VarQEC produces resource‑efficient codes that outperform standard codes and provide proof‑of‑concept experiments on IBM and IQM hardware.