Quantification of coarse-graining error in Langevin and overdamped Langevin dynamics

Research output: Contribution to journalArticlepeer-review

Standard

Quantification of coarse-graining error in Langevin and overdamped Langevin dynamics. / Duong, Hong; Lamacz, Agnes ; Peletier, Mark A. ; Schlichting, André ; Sharma, Upanshu .

In: Nonlinearity, Vol. 31, No. 10, 01.10.2018, p. 4517-4566.

Research output: Contribution to journalArticlepeer-review

Harvard

Duong, H, Lamacz, A, Peletier, MA, Schlichting, A & Sharma, U 2018, 'Quantification of coarse-graining error in Langevin and overdamped Langevin dynamics', Nonlinearity, vol. 31, no. 10, pp. 4517-4566. https://doi.org/10.1088/1361-6544/aaced5

APA

Vancouver

Author

Duong, Hong ; Lamacz, Agnes ; Peletier, Mark A. ; Schlichting, André ; Sharma, Upanshu . / Quantification of coarse-graining error in Langevin and overdamped Langevin dynamics. In: Nonlinearity. 2018 ; Vol. 31, No. 10. pp. 4517-4566.

Bibtex

@article{308aa68112c941c29e992b86b1d2cabe,
title = "Quantification of coarse-graining error in Langevin and overdamped Langevin dynamics",
abstract = "In molecular dynamics and sampling of high dimensional Gibbs measures coarse-graining is an important technique to reduce the dimensionality of the problem. We will study and quantify the coarse-graining error between the coarse-grained dynamics and an effective dynamics. The effective dynamics is a Markov process on the coarse-grained state space obtained by a closure procedure from the coarse-grained coefficients. We obtain error estimates both in relative entropy and Wasserstein distance, for both Langevin and overdamped Langevin dynamics. The approach allows for vectorial coarse-graining maps. Hereby, the quality of the chosen coarse-graining is measured by certainfunctional inequalities encoding the scale separation of the Gibbs measure. The method is based on error estimates between solutions of (kinetic) Fokker-Planck equations in terms of large-deviation rate functionals.",
keywords = "coarse-graining, relative entropy techniques, effective dynamics for SDEs, functional inequalities, Langevin equation, large-deviation rate functionals",
author = "Hong Duong and Agnes Lamacz and Peletier, {Mark A.} and Andr{\'e} Schlichting and Upanshu Sharma",
year = "2018",
month = oct,
day = "1",
doi = "10.1088/1361-6544/aaced5",
language = "English",
volume = "31",
pages = "4517--4566",
journal = "Nonlinearity",
issn = "0951-7715",
publisher = "IOP Publishing",
number = "10",

}

RIS

TY - JOUR

T1 - Quantification of coarse-graining error in Langevin and overdamped Langevin dynamics

AU - Duong, Hong

AU - Lamacz, Agnes

AU - Peletier, Mark A.

AU - Schlichting, André

AU - Sharma, Upanshu

PY - 2018/10/1

Y1 - 2018/10/1

N2 - In molecular dynamics and sampling of high dimensional Gibbs measures coarse-graining is an important technique to reduce the dimensionality of the problem. We will study and quantify the coarse-graining error between the coarse-grained dynamics and an effective dynamics. The effective dynamics is a Markov process on the coarse-grained state space obtained by a closure procedure from the coarse-grained coefficients. We obtain error estimates both in relative entropy and Wasserstein distance, for both Langevin and overdamped Langevin dynamics. The approach allows for vectorial coarse-graining maps. Hereby, the quality of the chosen coarse-graining is measured by certainfunctional inequalities encoding the scale separation of the Gibbs measure. The method is based on error estimates between solutions of (kinetic) Fokker-Planck equations in terms of large-deviation rate functionals.

AB - In molecular dynamics and sampling of high dimensional Gibbs measures coarse-graining is an important technique to reduce the dimensionality of the problem. We will study and quantify the coarse-graining error between the coarse-grained dynamics and an effective dynamics. The effective dynamics is a Markov process on the coarse-grained state space obtained by a closure procedure from the coarse-grained coefficients. We obtain error estimates both in relative entropy and Wasserstein distance, for both Langevin and overdamped Langevin dynamics. The approach allows for vectorial coarse-graining maps. Hereby, the quality of the chosen coarse-graining is measured by certainfunctional inequalities encoding the scale separation of the Gibbs measure. The method is based on error estimates between solutions of (kinetic) Fokker-Planck equations in terms of large-deviation rate functionals.

KW - coarse-graining

KW - relative entropy techniques

KW - effective dynamics for SDEs

KW - functional inequalities

KW - Langevin equation

KW - large-deviation rate functionals

U2 - 10.1088/1361-6544/aaced5

DO - 10.1088/1361-6544/aaced5

M3 - Article

VL - 31

SP - 4517

EP - 4566

JO - Nonlinearity

JF - Nonlinearity

SN - 0951-7715

IS - 10

ER -