Coarse-graining Langevin dynamics using reduced-order techniques

Coarse-graining Langevin dynamics using reduced-order techniques
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使用降阶技术的粗粒度 Langevin 动力学

DOI:
10.1016/j.jcp.2018.11.035
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发表时间:
2019
影响因子:
4.1
通讯作者:
Liu, Chun
Liu, Chun
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
Ma, Lina;Li, Xiantao;Liu, Chun

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本文考虑了生物分子模型中朗之万方程的约化问题。为了便于简化模型的构建和实现,将问题转化为降阶建模问题。然后,可以直接从Galerkin投影到适当定义的Krylov子空间中获得简化模型。证明了与[32]中实现的矩匹配过程的等价性。一个特别强调的是放在减少随机噪声,这是缺乏在许多订单减少问题。特别地,对于阶数小于6的情形,我们可以证明从子空间投影得到的简化模型自动满足涨落耗散定理。还将讨论实现的细节,包括双正交化过程和矩阵乘法的数量的最小化。
This paper considers the reduction of the Langevin equation arising from bio-molecular models. To facilitate the construction and implementation of the reduced models, the problem is formulated as a reduced-order modeling problem. The reduced models can then be directly obtained from a Galerkin projection to appropriately defined Krylov subspaces. The equivalence to a moment-matching procedure, previously implemented in [32], is proved. A particular emphasis is placed on the reduction of the stochastic noise, which is absent in many order-reduction problems. In particular, for order less than six we can show the reduced model obtained from the subspace projection automatically satisfies the fluctuation-dissipation theorem. Details for the implementations, including a bi-orthogonalization procedure and the minimization of the number of matrix multiplications, will be discussed as well.
DOI: 10.1007/b95265
发表时间: 2013-10
期刊: --
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