A 3D convolutional neural network decoder for surface codes with circuit noise generalizes to distance-97 codes with thresholds up to 0.7% depolarizing noise and improved latency over MWPM above distance 33.
Advantage of quantum neural networks as quantum information decoders
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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.
The paper compiles a curated handbook reference of error-correcting codes, their symbol-based classifications, and interrelations with mathematical objects and physical phases.
citing papers explorer
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Fully convolutional 3D neural network decoders for surface codes with syndrome circuit noise
A 3D convolutional neural network decoder for surface codes with circuit noise generalizes to distance-97 codes with thresholds up to 0.7% depolarizing noise and improved latency over MWPM above distance 33.
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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.
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Handbook of Error-Correcting Codes
The paper compiles a curated handbook reference of error-correcting codes, their symbol-based classifications, and interrelations with mathematical objects and physical phases.