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arXiv 2602.03099quant-ph
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通过哈密顿嵌入实现资源高效的传输现象量子模拟

Resource-efficient quantum simulation of transport phenomena via Hamiltonian embedding

University of Maryland, College Park(马里兰大学帕克分校);Joint Center for Quantum Information and Computer Science(量子信息与计算科学联合中心);Simons Institute for the Theory of Computing, UC Berkeley(加州大学伯克利分校西蒙斯计算理论研究所);UC Berkeley(加州大学伯克利分校)

Joseph Li, Gengzhi Yang, Jiaqi Leng, Xiaodi Wu

AI总结:

本文提出了一种通过哈密顿嵌入技术实现资源高效模拟传输现象的框架,展示了在量子硬件上求解线性和非线性传输偏微分方程的实验成果。

摘要:

传输现象在许多应用领域中起着关键作用,高效模拟这些动力学过程仍然是一个突出的挑战。尽管量子计算机有带来显著加速的潜力,但现有算法要么缺乏严谨的理论保证,要么需要大量的量子资源,这阻碍了在现实量子硬件上可扩展和高效验证。为了解决这一差距,我们开发了一个全面的框架,用于模拟传输方程的某些类别,提供了严谨的理论保证——包括特定情况下的指数级加速——以及系统且硬件高效的实现。我们方法的核心是哈密顿嵌入技术,这是一种白盒方法,用于稀疏哈密顿量的端到端模拟,避免了抽象查询模型并保留了近最优的渐进行为。实证资源估计表明,我们的方法在有利的问题结构下可以带来数量级(例如,42倍)的电路深度减少。我们然后将该框架应用于求解线性和非线性传输偏微分方程,包括在囚禁离子量子计算机上首次实验演示的二维输运方程。

英文摘要:

Transport phenomena play a key role in a variety of application domains, and efficient simulation of these dynamics remains an outstanding challenge. While quantum computers offer potential for significant speedups, existing algorithms either lack rigorous theoretical guarantees or demand substantial quantum resources, preventing scalable and efficient validation on realistic quantum hardware. To address this gap, we develop a comprehensive framework for simulating classes of transport equations, offering both rigorous theoretical guarantees -- including exponential speedups in specific cases -- and a systematic, hardware-efficient implementation. Central to our approach is the Hamiltonian embedding technique, a white-box approach for end-to-end simulation of sparse Hamiltonians that avoids abstract query models and retains near-optimal asymptotic complexity. Empirical resource estimates indicate that our approach can yield an order-of-magnitude (e.g., $42\times$) reduction in circuit depth given favorable problem structures. We then apply our framework to solve linear and nonlinear transport PDEs, including the first experimental demonstration of a 2D advection equation on a trapped-ion quantum computer.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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