发表机构
Institute of Engineering Thermodynamics, German Aerospace Center (DLR); Helmholtz Institute Ulm; Department of Physics, Ulm University（德国航空航天中心工程热力学研究所; 乌尔姆亥姆霍兹研究所; 乌尔姆大学物理系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种混合量子-经典算法，可扩展地求解非线性偏微分方程，并首次实现对带电解质单粒子模型（SPMe）电池单元的量子模拟，以加速电化学系统研究。
AI 中文摘要
电化学材料和系统的模拟加速了技术进步，但仍受限于计算能力。特别是，量子计算由于量子态中可存储的数据量呈指数级增长，为更高分辨率提供了前景。由于当前量子计算机仍存在噪声，我们考虑一种混合量子-经典算法，将问题划分为较小的计算任务。我们描述了如何以可扩展的方式为电化学系统实现这种用于非线性偏微分方程（Feynman-Kitaev Hamiltonian）的算法。我们展示了它如何评估通用电化学模型，并呈现了带电解质单粒子模型（SPMe）的量子模拟，这是电池单元的首次量子模拟。
英文摘要
Simulations of electrochemical materials and systems accelerate technological progress, but are still limited by computational power. In particular, quantum computing offers prospects for higher resolutions, due to the exponential amount of data that can be stored in a quantum state. As current quantum computers are still noisy, we consider a hybrid quantum-classical algorithm, that divides the problem into smaller computational tasks. We describe how to implement such an algorithm for non-linear partial differential equations, the Feynman-Kitaev Hamiltonian, in a scalable way for an electrochemical system. We show how it can evaluate general electrochemical models and present a quantum simulation of the Single Particle Model with electrolyte (SPMe) as the first quantum simulation of a battery cell.
Comments9 pages, 5 figures
