No. 03
量子伊辛模型中长程相互作用与耗散的博弈Interplay between long-range interactions and dissipation in quantum Ising model
将长程相互作用量子伊辛模型拓展到开放系统,发现长程作用既能稳定铁磁畴、抑制噪声,又使每个自旋间接暴露于更大环境而加速记忆丧失,弱耗散下呈现依赖初态的丰富弛豫动力学。
长程相互作用模型展现出由偏离集体描述所驱动的丰富动力学现象。本工作将这些模型的研究拓展至开放量子系统,聚焦于非局域相互作用与局域耗散之间复杂的相互作用。结果表明,长程相互作用对弛豫的影响具有两面性:它们通过稳定铁磁畴、减小局域涨落来抑制噪声的影响,但同时通过间接使每个自旋暴露于更广阔的环境而加速记忆丧失。强耗散将系统驱入玻璃态、对作用范围不敏感的弛豫,而弱耗散区的结果则揭示出丰富的依赖状态的动力学。具体而言,长程集体行为保护了从极化态淬火后的系统早期相干性,却主动加速交错位形的弛豫。此外,即使在耗散淬火的近稳态阶段,非局域相互作用仍持续驱动记忆退关联。这些发现为使用长程相互作用的模拟量子模拟器的设计、控制和校准提供了及时的理论洞见。
Abstract (English)
Long-range interacting models exhibit rich dynamical phenomena driven by deviations from collective descriptions. This work extends the study of these models to open quantum systems, focusing on the complex interplay between nonlocal interactions and local dissipation. The results demonstrate that the impact of long-range interactions on relaxation is twofold: they mitigate the impact of noises by stabilizing ferromagnetic domains and reducing local fluctuation, yet simultaneously accelerate memory loss by indirectly exposing each spin to a broader environment. While strong dissipation drives the system into glassy, range-insensitive relaxation, the results in weak dissipation regime reveal rich state-dependent dynamics. Specifically, long-range collective behaviors protect the early-stage coherence of systems quenched from polarized states, whereas they actively accelerate the relaxation of staggered configurations. Furthermore, nonlocal interactions continue to drive memory decorrelation even in the near-steady stages of a dissipative quench. These findings offer timely theoretical insights for the design, control, and calibration of analog quantum simulators operating with long-range interactions.
Zewen Zhang
Quantum Review Letters 2, 185-193 (2026)
10.1016/j.qrl.2026.08.002
No. 04
QPanda 3.0:面向大规模量子程序的可扩展高性能编译框架QPanda 3.0: A scalable and high performance compilation framework for large scale quantum programs
提出高性能量子编程框架QPanda 3.0,通过优化编译流水线、自定义二进制指令流与硬件感知执行策略,编码和解码较OpenQASM 2.0最高分别快86.9倍和35.6倍,较Qiskit平均编译加速10.7倍。
量子计算有望在某些问题类别上相较经典方法实现计算加速;然而在近期量子与经典混合工作流中,整体性能常受经典处理开销制约。电路编译(包括门分解、拓扑感知的量子比特映射和深度优化)以及电路传输、测量结果交换等协议层通信所带来的时间成本,常常超过实际量子电路执行时间,已成为实际部署的关键瓶颈。本文提出QPanda 3.0,一个高性能量子编程框架,针对支撑NISQ时代混合集成的经典编译路径进行加速优化。借助优化的编译流水线、自定义二进制指令流(OriginBIS)和硬件感知执行策略,QPanda 3.0相比OpenQASM 2.0的编码速度最高提升86.9倍、解码速度最高提升35.6倍,并在四种评估的连通拓扑上相较Qiskit平均实现10.7倍编译加速,其中在方形拓扑上118量子比特W态电路的最高加速达597倍。这些能力使得在金融、材料科学和组合优化等多个领域开发可扩展量子算法成为可能,并支持混合计算环境中的工业部署与云端执行。
Abstract (English)
Quantum computing promises computational speedups over classical approaches for certain problem classes; however, in near term quantum and classical hybrid workflows, the overall performance is often constrained by classical processing overhead. The time cost associated with circuit compilation, which includes gate decomposition, topology aware qubit mapping, and depth optimization, together with protocol level communication such as circuit transfer and measurement result exchange, frequently exceeds the actual quantum circuit execution time and has become a critical bottleneck to practical deployment. In this paper, we propose QPanda 3.0, a high performance quantum programming framework optimized to accelerate the classical compilation path that underpins NISQ era hybrid integration. Leveraging an optimized compilation pipeline, a custom binary instruction stream (OriginBIS), and hardware aware execution strategies, QPanda 3.0 achieves up to 86.9 × faster encoding and 35.6 × faster decoding than OpenQASM 2.0, as well as an average 10.7 × compilation speedup over Qiskit across the four evaluated connectivity topologies, with a peak speedup of 597 × for a 118-qubit W-state circuit on a square topology. These capabilities enable the development of scalable quantum algorithms across various domains, including finance, materials science, and combinatorial optimization, supporting both industrial deployment and cloud based execution in hybrid computing environments.
Tian-Rui Zou, Yuan Fang, Jing Wang, Jun Fu, Shu-Bin Zhao, Lei Yu, Dong-Yi Zhao, Hui Wang, Chun-Yun Zhao, Yun Ma, Chuang-Shi Ma, Bin Ye, Ning Gao, Chun-Lin Wan, Meng-Han Dou, Zhao-Yun Chen, Guo-Ping Guo
Quantum Review Letters 2, 172-184 (2026)
10.1016/j.qrl.2026.08.001