论文标题
对粗粒模型中记忆项的系统分析：马尔可夫近似的情况
A Systematic Analysis of the Memory term in Coarse-Grained models: the case of the Markovian Approximation
论文作者
论文摘要
通过Mori-Zwanzig投影仪运算符形式主义的粗粒（CG）模型的系统开发需要对几个术语进行明确描述，包括确定性漂移项，耗散记忆项和随机波动项。在许多应用中，记忆和波动项是通过波动散落关系相关的，通常比漂移期更具挑战性。在这项工作中，我们分析了记忆项的近似值，并为数据驱动的方法提出了合理的基础，以实现记忆和波动项的近似值，这些术语可被认为包括在马尔可夫阶层中。
The systematic development of Coarse-Grained (CG) models via the Mori-Zwanzig projector operator formalism requires the explicit description of several terms, including a deterministic drift term, a dissipative memory term and a random fluctuation term. In many applications, the memory and fluctuation terms are related by the fluctuation-dissipation relation and are, in general, more challenging to derive than the drift term. In this work we analyse an approximation of the memory term and propose a rational basis for a data-driven approach to an approximation of the memory and fluctuating terms which can be considered included in the class of the Markovian ones.
