7 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…
SurgeQ: A Hybrid Framework for Ultra-Fast Quantum Processor Design and Crosstalk-Aware Circuit Execution
Xinxuan Chen, Hongxiang Zhu, Zhaohui Yang +4
Executing quantum circuits on superconducting platforms requires balancing the trade-off between gate errors and crosstalk. To address this, we introduce SurgeQ, a hardware-softwar…
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…
Breaking the Treewidth Barrier in Quantum Circuit Simulation with Decision Diagrams
Bin Cheng, Ziyuan Wang, Ruixuan Deng +2
Classical simulation of quantum circuits is a critical tool for validating quantum hardware and probing the boundary between classical and quantum computational power. Existing sta…
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…