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Feng Pan

10 papers hereh-index 435 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author6
  • last author2

Across the 9 of 10 papers where every author was matched, so the position is known.

fields
  • quant-ph6
  • cond-mat.stat-mech3
  • cs.DC1
same name
  • Feng Pan — 16 papers, h 11
  • Feng Pan — 13 papers, h 11
  • Feng Pan — 8 papers, h 15
  • Feng Pan — 8 papers, h 15
  • Feng Pan — 7 papers, h 85
  • Feng Pan — 4 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedGenerative Decoding for Quantum Error-correcting Codes

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

collaborators
Showing 2026 · quant-phShow all

4 papers · 2 filters

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…

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…

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.