Adaptive window decoding with spatiotemporal complementary gap reduces average buffer size by 40% while maintaining logical error rate in quantum error correction simulations.
Even more efficient soft-output decoding with extra-cluster growth and early stopping.arXiv preprint arXiv:2602.03336, 2026
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GNN decoder logit outperforms MWPM logical gap for post-selection, yielding lower logical error rates on surface code syndromes under circuit-level noise.
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Adaptive Window Decoding based on Spatiotemporal Complementary Gap
Adaptive window decoding with spatiotemporal complementary gap reduces average buffer size by 40% while maintaining logical error rate in quantum error correction simulations.
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Neural network decoder confidence as a learned proxy for the logical gap
GNN decoder logit outperforms MWPM logical gap for post-selection, yielding lower logical error rates on surface code syndromes under circuit-level noise.