Repository: Freie Universität Berlin, Math Department

An efficient multi-scale Green's Functions Reaction Dynamics scheme

Sbailò, L. and Noé, F. (2017) An efficient multi-scale Green's Functions Reaction Dynamics scheme. J. Chem. Phys., 147 . p. 184106. ISSN 0021-9606, ESSN: 1089-7690

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Molecular Dynamics-Green’s Function Reaction Dynamics (MD-GFRD) is a multiscale simulation method for particle dynamics or particle-based reaction-diffusion dynamics that is suited for systems involving low particle densities. Particles in a low-density region are just diffusing and not interacting. In this case, one can avoid the costly integration of microscopic equations of motion, such as molecular dynamics (MD), and instead turn to an event-based scheme in which the times to the next particle interaction and the new particle positions at that time can be sampled. At high (local) concentrations, however, e.g., when particles are interacting in a nontrivial way, particle positions must still be updated with small time steps of the microscopic dynamical equations. The efficiency of a multi-scale simulation that uses these two schemes largely depends on the coupling between them and the decisions when to switch between the two scales. Here we present an efficient scheme for multi-scale MD-GFRD simulations. It has been shown that MD-GFRD schemes are more efficient than brute-force molecular dynamics simulations up to a molar concentration of 102 μM. In this paper, we show that the choice of the propagation domains has a relevant impact on the computational performance. Domains are constructed using a local optimization of their sizes and a minimal domain size is proposed. The algorithm is shown to be more efficient than brute-force Brownian dynamics simulations up to a molar concentration of 103 μM and is up to an order of magnitude more efficient compared with previous MD-GFRD schemes.

Item Type:Article
Additional Information:kein Preprint vorhanden
Subjects:Physical Sciences
Physical Sciences > Chemistry
Physical Sciences > Chemistry > Physical Chemistry
Mathematical and Computer Sciences
Divisions:Department of Mathematics and Computer Science > Institute of Mathematics > Comp. Molecular Biology
ID Code:2123
Deposited By: BioComp Admin
Deposited On:24 Oct 2017 13:10
Last Modified:06 Jun 2019 14:37

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