记忆核耦合理论中的广义量子主方程
Generalized quantum master equation from memory kernel coupling theory
AI总结：
提出张量扩展的记忆核耦合理论（MKCT），通过将标量形式提升为张量框架，高效计算开放量子系统的非马尔可夫动力学，包括期望值、关联函数，并在自旋-玻色子模型、Fenna-Matthews-Olson复合物和晶格模型中验证了其准确性和效率。
摘要：
广义量子主方程为开放量子系统的非马尔可夫动力学提供了强大框架。然而，记忆核的准确高效评估仍是一个挑战。在本工作中，我们引入了记忆核耦合理论（MKCT）的全面张量扩展以克服这一瓶颈。通过将原始标量形式提升为张量框架，扩展的MKCT能够计算一般期望值和互相关函数。我们在多个基准系统中展示了该方法的数值准确性和效率：捕捉自旋-玻色子模型中的瞬态布居和相干性，解析Fenna-Matthews-Olson复合物的激子吸收光谱，以及模拟一维晶格模型中的电荷迁移率。这些成功应用确立了张量MKCT作为研究开放量子系统中复杂动力学的高效工具。
英文摘要：
The generalized quantum master equation provides a powerful framework for non-Markovian dynamics of open quantum systems. However, the accurate and efficient evaluation of the memory kernel remains a challenge. In this work, we introduce a comprehensive tensorial extension to the Memory Kernel Coupling Theory (MKCT) to overcome this bottleneck. By elevating the original scalar formalism to a tensorial framework, the extended MKCT enables the calculation of general expectation values and cross-correlation functions. We demonstrate the numerical accuracy and efficiency of this method across multiple benchmark systems: capturing transient populations and coherences in the spin-boson model, resolving the excitonic absorption spectrum of the Fenna-Matthews-Olson complex, and simulating charge mobility in one-dimensional lattice models. These successful applications establish the tensorial MKCT as a highly efficient tool for investigating complex dynamics in open quantum systems.
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