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Sampling diffusive transition paths

机译:采样扩散过渡路径

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The authors address the problem of sampling double-ended diffusive paths.The ensemble of paths is expressed using a symmetric version of the Onsager-Machlup formula,which only requires evaluation of the force field and which,upon direct time discretization,gives rise to a symmetric integrator that is accurate to second order.Efficiently sampling this ensemble requires avoiding the well-known stiffness problem associated with the sampling of infinitesimal Brownian increments of the path,as well as a different type of stiffness associated with the sampling of the coarse features of long paths.The fine-feature sampling stiffness is eliminated with the use of the fast sampling algorithm,and the coarse-feature sampling stiffness is avoided by introducing the sliding and sampling(S&S)algorithm.A key feature of the S&S algorithm is that it enables massively parallel computers to sample diffusive trajectories that are long in time.The authors use the algorithm to sample the transition path ensemble for the structural interconversion of the 38-atom Lennard-Jones cluster at low temperature.
机译:作者解决了对双端扩散路径进行采样的问题。路径的合集使用Onsager-Machlup公式的对称形式表示,该公式仅需要评估力场,并且在直接时间离散化时,得出有效地对该集合进行采样需要避免与路径的无穷小布朗增量采样相关的众所周知的刚度问题,以及与采样粗糙特征相关的不同类型的刚度。快速采样算法消除了精细特征的采样刚度,引入了滑动和采样(S&S)算法避免了粗略特征的采样刚度.S&S算法的一个关键特性是使大型并行计算机能够对漫长的扩散轨迹进行采样。作者使用该算法对过渡路径ens进行采样。为低温下38原子Lennard-Jones团簇的结构互变提供了便利。

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