Coarse-graining Langevin dynamics using reduced-order techniques

JOURNAL OF COMPUTATIONAL PHYSICS

卷:380

Article

Ma, Lina¹  Li, Xiantao²  Liu, Chun³ 

[1] Trinity Coll, Dept Math, Hartford, CT 06106 USA

[2] Penn State Univ, Dept Math, University Pk, PA 16802 USA

[3] IIT, Dept Appl Math, Chicago, IL 60616 USA

关键词: Coarse graining;    Reduced order;    Krylov subspace;    The fluctuation dissipation theorem;   

DOI  :  10.1016/j.jcp.2018.11.035

来源: Elsevier

【 摘 要 】

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 biorthogonalization procedure and the minimization of the number of matrix multiplications, will be discussed as well. (C) 2018 Elsevier Inc. All rights reserved.

【 授权许可】

Free