标题： 从维数约简技术得到的聚合物动力学模型 显示英文标题

标题： Models for polymer dynamics from dimensionality reduction techniques

摘要： 通过线性降维方法分析聚合物动力学，特别是主成分分析（PCA）和时滞独立成分分析（tICA）。 对于经历理想Rouse动力学的聚合物，这些变换识别出的慢模式与传统的Rouse模式一致。 当应用于段密度的傅里叶模式时，我们表明tICA生成的动力学等价于具有波矢依赖的Onsager系数和受随机相位近似（RPA）约束的自由能泛函的动态自洽场理论（D-SCFT）。 然后我们引入一种隐变量方法和一种时间局部方法，以在tICA生成的动力学中包含时间记忆，并将其推广以构建对称二嵌段共聚物熔体旋节分解非平衡情况的连续模型。 显示英文摘要

摘要： Polymer dynamics is analyzed through the lens of linear dimensionality reduction methods, in particular principal (PCA) and time-lagged independent component analysis (tICA). For a polymer undergoing ideal Rouse dynamics, the slow modes identified by these transformations coincide with the conventional Rouse modes. When applied to the Fourier modes of the segment density, we show that tICA generates dynamics equivalent to dynamic self-consistent field theory (D-SCFT) with a wavevector-dependent Onsager coefficient and a free energy functional subject to the random phase approximation (RPA). We then introduce a hidden variable method and a time-local approach to include temporal memory in the tICA-generated dynamics, and generalize it to construct continuum models for the nonequilibrium case of spinodal decomposition of a symmetric diblock copolymer melt.