Analysis of the Dynamics in Linear Chain Models by means of Generalized Langevin Equations

IF 1.3 3区 物理与天体物理 Q3 PHYSICS, MATHEMATICAL Journal of Statistical Physics Pub Date : 2024-05-04 DOI:10.1007/s10955-024-03274-z
Fabian Koch, Suvendu Mandal, Tanja Schilling
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Abstract

We analyse the motion of one particle in a polymer chain. For this purpose, we use the framework of the exact (non-stationary) generalized Langevin equation that can be derived from first principles via the projection-operator method. Our focus lies on determining memory kernels from either exact expressions for autocorrelation functions or from simulation data. We increase the complexity of the underlying system starting out from one-dimensional harmonic chains and ending with a polymer driven through a polymer melt. Here, the displacement or the velocity of an individual particle in the chain serves as the observable. The central result is that the time-window in which the memory kernels show structure before they rapidly decay decreases with increasing complexity of the system.

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利用广义朗文方程分析线性链模型的动态性
我们分析了聚合物链中一个粒子的运动。为此,我们使用了精确(非稳态)广义朗之文方程的框架,该方程可通过投影操作法从第一原理推导出来。我们的重点是根据自相关函数的精确表达式或模拟数据确定记忆核。我们增加了底层系统的复杂性,从一维谐波链开始,到聚合物熔体中的聚合物。在这里,链中单个粒子的位移或速度可作为观测值。其核心结果是,随着系统复杂度的增加,记忆核在快速衰减前显示结构的时间窗口会减小。
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来源期刊
Journal of Statistical Physics
Journal of Statistical Physics 物理-物理:数学物理
CiteScore
3.10
自引率
12.50%
发文量
152
审稿时长
3-6 weeks
期刊介绍: The Journal of Statistical Physics publishes original and invited review papers in all areas of statistical physics as well as in related fields concerned with collective phenomena in physical systems.
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