8 papers
OmniQEC: discovering practical quantum error-correcting codes by an AI scientist
Ge Yan, Shanchuan Li, Pengyue Ma +5
Quantum error correction (QEC) is indispensable for scalable fault-tolerant quantum computing. However, discovering QEC codes that remain effective is challenging, as logical perfo…
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…
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…
Rethink the Role of Neural Decoders in Quantum Error Correction
Ge Yan, Shanchuan Li, Yuxuan Du
Quantum error correction (QEC) is essential for enabling quantum advantages, with decoding as a central algorithmic primitive. Owing to its importance and intrinsic difficulty, sub…
Universal 2-Local Symmetry-Preserving Quantum Neural Networks for Fermionic Systems
Ge Yan, Kaisen Pan, Ruocheng Wang +3
Simulating quantum many-body systems represents a fundamental challenge where classical machine learning methods are severely bottlenecked by the exponential curse of dimensionalit…
Sample-efficient quantum error mitigation via classical learning surrogates
Wei-You Liao, Ge Yan, Yujin Song +5
The pursuit of practical quantum utility on near-term quantum processors is critically challenged by their inherent noise. Quantum error mitigation (QEM) techniques are leading sol…