拓扑量子硬件上量子动力学的可扩展模拟
Scalable Simulation of Quantum Dynamics on Topological Quantum Hardware
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中文总结 AI 辅助
本研究提出一个在拓扑量子硬件上模拟量子动力学的框架，利用非阿贝尔任意子和Solovay-Kitaev算法，实现对多体凝聚相系统的高效可扩展模拟。
中文摘要 AI 辅助
量子计算机在模拟量子系统方面相较于经典计算机具有显著优势，尽管目前大多数应用仅限于使用混合量子-经典硬件计算静态分子性质。在本工作中，我们建立了一个用于分子和凝聚态系统中量子动力学表示的框架，该框架专为在拓扑量子硬件上执行而设计。通过利用Fibonacci和Ising任意子的非阿贝尔编织统计，我们采用Solovay-Kitaev算法来近似一系列系统的酉传播子。我们在一系列复杂度层级上展示了这些算法的有效性，从二能级系统和一维双阱势，到凝聚相自旋-玻色子模型、简单分子以及分子反应动力学。这些算法为在容错量子设备上模拟多体凝聚相化学物理提供了一条可扩展且稳健的途径。
英文摘要
Quantum computers offer a significant advantage in simulating quantum systems compared to classical computers for certain problems, although most current applications are limited to calculating static molecular properties using hybrid quantum-classical hardware. In this work, we establish a framework for the representation of quantum dynamics in molecular and condensed matter systems, designed for execution on topological quantum hardware. By leveraging the non-Abelian braiding statistics of Fibonacci and Ising anyons, we utilize the Solovay-Kitaev algorithm to approximate unitary propagators for a range of systems. We demonstrate the efficacy of these algorithms across a hierarchy of complexity, from two-level systems and one dimensional double-well potentials to condensed phase spin-boson models, simple molecules, and molecular reaction kinetics. These algorithms provide a scalable and robust pathway for simulating many-body condensed phase chemical physics on fault-tolerant quantum devices.
发表机构
- New York University（纽约大学）
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai（上海纽约大学纽-华东师范大学计算化学中心）
机构由 AI 辅助整理，请以论文原文为准。
