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20242026
most citedGenerative Decoding for Quantum Error-correcting Codes

1 citations · 1 across the 9 of their papers we have counts for

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10 papers

quant-ph2026

Exact Maximum Likelihood Decoding beyond Treewidth via Rank-Decomposition Dynamic Programming

Bin Cheng, Feng Pan

Maximum-likelihood decoding provides an optimal decoding strategy for quantum error correction under stochastic Pauli noise. However, computing logical-class probabilities is chall…

quant-ph2026

Efficient foundation decoders for fault-tolerant quantum computing

Ge Yan, Shanchuan Li, Shiyi Xiao +4

Foundation decoders, a class of high-capacity neural decoders, are leading candidates for fault-tolerant quantum computing, with accurate and efficient decoding at large code dista…

cs.DC2026

Parallelizing Large-Scale Tensor Network Contraction on Multiple GPUs

Feng Pan, Hanfeng Gu, Paul Springer +1

Exact tensor network contraction underpins quantum circuit simulation, quantum error correction, combinatorial optimization, and many-body dynamics. The dominant parallelization st…

quant-ph2026

Maximum Likelihood Decoding of Quantum Error Correction Codes

Hanyan Cao, Ge Yan, Yuxuan Du +1

Quantum error correction (QEC) is indispensable for realizing fault-tolerant quantum computation, yet its effectiveness hinges critically on the classical decoding algorithm that i…

cond-mat.stat-mech2026

Branch-and-Bound Tensor Networks for Exact Ground-State Characterization

Yijia Wang, Xuanzhao Gao, Pan Zhang +2

Characterizing the ground-state properties of disordered systems, such as spin glasses and combinatorial optimization problems, is fundamental to science and engineering. However,…

quant-ph2026

Differentiable Maximum Likelihood Noise Estimation for Quantum Error Correction

Hanyan Cao, Dongyang Feng, Cheng Ye +2

Accurate noise estimation is essential for fault-tolerant quantum computing, since decoding per formance depends critically on the fidelity of circuit-level noise parameters. We in…

cond-mat.stat-mech2025

Integrating Neural Networks and Tensor Networks for Computing Free Energy

Hanyan Cao, Yijia Wang, Feng Pan +1

Computing free energy is a fundamental problem in statistical physics. Recently, two distinct methods have been developed and have demonstrated remarkable success: the tensor-netwo…

quant-ph2025★ 1 cited

Generative Decoding for Quantum Error-correcting Codes

Hanyan Cao, Feng Pan, Dongyang Feng +2

Efficient and accurate decoding of quantum error-correcting codes is essential for fault-tolerant quantum computation, however, it is challenging due to the degeneracy of errors, t…

quant-ph2025

Exact Decoding of Repetition Code under Circuit Level Noise

Hanyan Cao, Shoukuan Zhao, Dongyang Feng +8

Repetition code forms a fundamental basis for quantum error correction experiments. To date, it stands as the sole code that has achieved large distances and extremely low error ra…

cond-mat.stat-mech2024

Free-Energy Machine for Combinatorial Optimization

Zi-Song Shen, Feng Pan, Yao Wang +4

Finding optimal solutions to combinatorial optimization problems is pivotal in both scientific and technological domains, within academic research and industrial applications. A co…