Sparse Mamba Decoder processes only active defects in surface code syndromes using a 13-feature representation and Mamba backbone for O(k) complexity, reporting speedups and accuracy gains over dense decoders.
Sparse blossom: correcting a million errors per core second with minimum-weight matching.Quantum, 9:1600, January 2025
6 Pith papers cite this work. Polarity classification is still indexing.
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FTPrimitiveBench is a new benchmark suite for testing surface-code logical primitives under Pauli-biased, measurement-biased, and spatially non-uniform noise models, revealing that noise structure interacts distinctly with each primitive and decoder.
Lottery BP adds randomness to belief propagation decoding and uses syndrome voting to achieve far higher accuracy on topological quantum codes while reducing reliance on expensive global decoders.
Local syndrome-based preprocessing accelerates BP decoders for quantum LDPC codes, delivering up to 10x speedup on the [[144,12,12]] code while maintaining or improving logical error rates.
MCMit mitigates mid-circuit measurement errors via a new multi-control branch instruction, CNN and transformer discriminators, and software techniques, reporting up to 70% latency reduction and 80% lower logical error rates in QEC.
A topical review unifying statistical mechanics, tensor network, and AI approaches to approximate maximum likelihood decoding for quantum error correction codes.
citing papers explorer
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Sparse Mamba Decoder for Quantum Error Correction: Efficient Defect-Centric Processing of Surface Code Syndromes
Sparse Mamba Decoder processes only active defects in surface code syndromes using a 13-feature representation and Mamba backbone for O(k) complexity, reporting speedups and accuracy gains over dense decoders.
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FTPrimitiveBench: A Benchmark Suite For Logical Computation Under Hardware-Motivated and Biased Noise Models
FTPrimitiveBench is a new benchmark suite for testing surface-code logical primitives under Pauli-biased, measurement-biased, and spatially non-uniform noise models, revealing that noise structure interacts distinctly with each primitive and decoder.
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Lottery BP: Unlocking Quantum Error Decoding at Scale
Lottery BP adds randomness to belief propagation decoding and uses syndrome voting to achieve far higher accuracy on topological quantum codes while reducing reliance on expensive global decoders.
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Accelerating BP-based decoders for QLDPC Codes with Local Syndrome-Based Preprocessing
Local syndrome-based preprocessing accelerates BP decoders for quantum LDPC codes, delivering up to 10x speedup on the [[144,12,12]] code while maintaining or improving logical error rates.
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MCMit: Mid-Circuit Measurement Error Mitigation
MCMit mitigates mid-circuit measurement errors via a new multi-control branch instruction, CNN and transformer discriminators, and software techniques, reporting up to 70% latency reduction and 80% lower logical error rates in QEC.
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Maximum Likelihood Decoding of Quantum Error Correction Codes
A topical review unifying statistical mechanics, tensor network, and AI approaches to approximate maximum likelihood decoding for quantum error correction codes.