Name
Abstract | ||
|---|---|---|
We propose a mathematical analysis of a well-known numerical approach used in molecular dynamics to efficiently sample a coarse-grained description of the original trajectory (in terms of state-to-state dynamics). This technique is called parallel replica dynamics and has been introduced by Arthur F. Voter. The principle is to introduce many replicas of the original dynamics, and to consider the first transition event observed among all the replicas. The effective physical time is obtained by summing up all the times elapsed for all replicas. Using a parallel implementation, a speed-up of the order of the number of replicas can thus be obtained, allowing longer time scales to be computed. By drawing connections with the theory of Markov processes and, in particular, exploiting the notion of quasi-stationary distribution, we provide a mathematical setting appropriate for assessing theoretically the performance of the approach, and possibly improving it. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1515/mcma-2012-0003 | MONTE CARLO METHODS AND APPLICATIONS |
Keywords | Field | DocType |
Parallel replica dynamics, quasi-stationary distribution, molecular dynamics | Replica,Markov process,Algorithm,Theoretical computer science,Molecular dynamics,Mathematics,Trajectory | Journal |
Volume | Issue | ISSN |
18 | 2 | 0929-9629 |
Citations | PageRank | References |
4 | 0.68 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| claude le bris | 1 | 33 | 9.83 |
| Tony Lelièvre | 2 | 33 | 9.48 |
| Mitchell Luskin | 3 | 124 | 23.89 |
| Danny Perez | 4 | 7 | 1.15 |