6 papers
Learning to Decode in Parallel: Self-Coordinating Neural Network for Real-Time Quantum Error Correction
Kai Zhang, Zhengzhong Yi, Shaojun Guo +13
Fast, reliable decoders are pivotal components for enabling fault-tolerant quantum computation (FTQC). Neural network decoders like AlphaQubit have demonstrated potential, achievin…
Quantum Design Automation: Foundations, Challenges, and the Road Ahead
Feng Wu, Jingzhe Guo, Tian Xia +12
Quantum computing is transitioning from laboratory research to industrial deployment, yet significant challenges persist: system scalability and performance, fabrication yields, an…
LATTE: A Decoding Architecture for Quantum Computing with Temporal and Spatial Scalability
Kai Zhang, Jubo Xu, Fang Zhang +3
Quantum error correction allows inherently noisy quantum devices to emulate an ideal quantum computer with reasonable resource overhead. As a crucial component, decoding architectu…
Learning Neural Decoding with Parallelism and Self-Coordination for Quantum Error Correction
Kai Zhang, Situ Wang, Linghang Kong +3
Fast, reliable decoders are pivotal components for enabling fault-tolerant quantum computation. Neural network decoders like AlphaQubit have demonstrated significant potential, ach…
Louvre: Relaxing Hardware Requirements of Quantum LDPC Codes by Routing with Expanded Quantum Instruction Set
Runshi Zhou, Fang Zhang, Hui-Hai Zhao +3
Generalized bicycle codes (GB codes) represent a promising family of quantum low-density parity-check codes, characterized by high code rates and relatively local qubit connectivit…
Convergence efficiency of quantum gates and circuits
Linghang Kong, Zimu Li, Zi-Wen Liu
We consider quantum circuit models where the gates are drawn from arbitrary gate ensembles given by probabilistic distributions over certain gate sets and circuit architectures, wh…