This work presents a systematic methodology for describing the transient dynamics of coarse-grained molecular systems inferred from all-atom simulated data. We suggest Langevin-type dynamics where the coarse-grained interaction potential depends explicitly on time to efficiently approximate the transient coarse-grained dynamics. We apply the path-space force matching approach at the transient dynamics regime to learn the proposed model parameters. In particular, we parameterize the coarse-grained potential both with respect to the pair distance of the CG particles and the time, and we obtain an evolution model that is explicitly time-dependent. Moreover, we follow a data-driven approach to estimate the friction kernel, given by appropriate correlation functions directly from the underlying all-atom molecular dynamics simulations. To explore and validate the proposed methodology we study a benchmark system of a moving particle in a box. We examine the suggested model's effectiveness in terms of the system's correlation time and find that the model can approximate well the transient time regime of the system, depending on the correlation time of the system. As a result, in the less correlated case, it can represent the dynamics for a longer time interval. We present an extensive study of our approach to a realistic high-dimensional water molecular system. Posing the water system initially out of thermal equilibrium we collect trajectories of all-atom data for the, empirically estimated, transient time regime. Then, we infer the suggested model and strengthen the model's validity by comparing it with simplified Markovian models.
翻译:这项工作为描述从全原子模拟数据中推断出的粗粒分子系统的瞬变动态提供了系统的方法。 我们建议使用粗粒互动潜力明确取决于时间的Langevin型动态,以便有效地接近瞬变粗粒粒子动态。 我们在瞬变动态系统中应用路径-空间力量匹配方法,以了解拟议的模型参数。 特别是, 我们将粗粒子潜力参数化, 以CG粒子和时间的对称距离为参数, 并获得一种明显依赖时间的进化模型。 此外, 我们采用数据驱动法, 以估算摩擦内核, 以来自基础的全原子分子动态模拟中的适当关联函数为根据。 为了探索和验证拟议方法, 我们研究一个在瞬变粒子中移动的基准系统, 我们从系统的相关时间模型的角度来考察所建议的模式的有效性, 并发现模型可以精确到系统的所有瞬变时间模型, 取决于系统的相关时间。 此外, 我们用数据驱动的跨度分析方法, 我们用一个不切实际的模型, 我们用一个更精确的模型, 我们用一个更精确的模型来测量一个更精确的系统, 我们用一个更精确的模型来测量的系统, 我们用一个更精确的模型来测测测测算。