2 citations · 3 across the 11 of their papers we have counts for
11 papers
Triage: An Adaptive Parallel Window Decoding Scheduler for Real-time Fault-Tolerant Quantum Computation
Jiahan Chen, Chenghong Zhu, Ge Bai +1
Fault-tolerant quantum computation (FTQC) critically depends on real-time classical decoding, which is rapidly emerging as a system bottleneck. As quantum systems scale, decoding l…
MUSS-TI: Multi-level Shuttle Scheduling for Large-Scale Entanglement Module Linked Trapped-Ion
Xian Wu, Chenghong Zhu, Jingbo Wang +1
Trapped-ion computing is a leading architecture in the pursuit of scalable and high fidelity quantum systems. Modular quantum architectures based on photonic interconnects offer a…
Quantum Compiler Design for Qubit Mapping and Routing: A Cross-Architectural Survey of Superconducting, Trapped-Ion, and Neutral Atom Systems
Chenghong Zhu, Xian Wu, Zhaohui Yang +4
Quantum hardware development is progressing rapidly with substantial advancements achieved across leading platforms, including superconducting circuits, trapped-ion systems, and ne…
Scalable Quantum Architecture Search via Landscape Analysis
Chenghong Zhu, Xian Wu, Hao-Kai Zhang +3
Balancing trainability and expressibility is a central challenge in variational quantum computing, and quantum architecture search (QAS) plays a pivotal role by automatically desig…
S-SYNC: Shuttle and Swap Co-Optimization in Quantum Charge-Coupled Devices
Chenghong Zhu, Xian Wu, Jingbo Wang +1
The Quantum Charge-Coupled Device (QCCD) architecture is a modular design to expand trapped-ion quantum computer that relies on the coherent shuttling of qubits across an array of…
Predicting symmetries of quantum dynamics with optimal samples
Masahito Hayashi, Yu-Ao Chen, Chenghong Zhu +1
Identifying symmetries in quantum dynamics, such as identity or time-reversal invariance, is a crucial challenge with profound implications for quantum technologies. We introduce a…
Optimizer-Dependent Generalization Bound for Quantum Neural Networks
Chenghong Zhu, Hongshun Yao, Yingjian Liu +1
Quantum neural networks (QNNs) play a pivotal role in addressing complex tasks within quantum machine learning, analogous to classical neural networks in deep learning. Ensuring co…
BOSS: Blocking algorithm for optimizing shuttling scheduling in Ion Trap
Xian Wu, Chenghong Zhu, Jingbo Wang +1
Ion traps stand at the forefront of quantum hardware technology, presenting unparalleled benefits for quantum computing, such as high-fidelity gates, extensive connectivity, and pr…
Hypothesis testing of symmetry in quantum dynamics
Yu-Ao Chen, Chenghong Zhu, Keming He +2
Symmetry plays a crucial role in quantum physics, dictating the behavior and dynamics of physical systems. In this paper, we develop a hypothesis-testing framework for quantum dyna…
Quantum Entanglement Allocation through a Central Hub
Yu-Ao Chen, Xia Liu, Chenghong Zhu +3
Establishing a fully functional quantum internet relies on the efficient allocation of multipartite entangled states, which enables advanced quantum communication protocols, secure…
Predicting quantum learnability from landscape fluctuation
Hao-Kai Zhang, Chenghong Zhu, Xin Wang
The conflict between trainability and expressibility is a key challenge in variational quantum computing and quantum machine learning. Resolving this conflict necessitates designin…