Estimating the speed-up of Adaptively Restrained Langevin Dynamics
| Autor: | Zofia Trstanova, Stephane Redon |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Numerical Analysis
Mathematical optimization Speedup Physics and Astronomy (miscellaneous) Computational complexity theory Statistical Mechanics (cond-mat.stat-mech) Applied Mathematics Computation Parameterized complexity FOS: Physical sciences 010103 numerical & computational mathematics Function (mathematics) 01 natural sciences Computer Science Applications Computational Mathematics Delta method Modeling and Simulation 0103 physical sciences Ergodic theory Statistical physics 0101 mathematics 010306 general physics Langevin dynamics Condensed Matter - Statistical Mechanics Mathematics |
| Popis: | We consider Adaptively Restrained Langevin dynamics, in which the kinetic energy function vanishes for small velocities. Properly parameterized, this dynamics makes it possible to reduce the computational complexity of updating inter-particle forces, and to accelerate the computation of ergodic averages of molecular simulations. In this paper, we analyze the influence of the method parameters on the total achievable speed-up. In particular, we estimate both the algorithmic speed-up, resulting from incremental force updates, and the influence of the change of the dynamics on the asymptotic variance. This allows us to propose a practical strategy for the parameterization of the method. We validate these theoretical results by representative numerical experiments. |
| Databáze: | OpenAIRE |
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