Many recently introduced enhanced sampling techniques are based on biasing coarse descriptors (collective variables) of a molecular system on the fly. Sometimes the calculation of such collective variables is expensive and becomes a bottleneck in molecular dynamics simulations. An algorithm to treat smooth biasing forces within a multiple time step framework is here discussed. The implementation is simple and allows a speed up when expensive collective variables are employed. The gain can be substantial when using massively parallel or GPU-based molecular dynamics software. Moreover, a theoretical framework to assess the sampling accuracy is introduced, which can be used to assess the choice of the integration time step in both single and multiple time step biased simulations.
Accurate multiple time step in biased molecular simulations / Ferrarotti, M. J.; Bottaro, Sandro; Perez Villa, Andrea; Bussi, Giovanni. - In: JOURNAL OF CHEMICAL THEORY AND COMPUTATION. - ISSN 1549-9618. - 11:1(2015), pp. 139-146. [10.1021/ct5007086]
Accurate multiple time step in biased molecular simulations
Bottaro, Sandro;Perez Villa, Andrea;Bussi, Giovanni
2015-01-01
Abstract
Many recently introduced enhanced sampling techniques are based on biasing coarse descriptors (collective variables) of a molecular system on the fly. Sometimes the calculation of such collective variables is expensive and becomes a bottleneck in molecular dynamics simulations. An algorithm to treat smooth biasing forces within a multiple time step framework is here discussed. The implementation is simple and allows a speed up when expensive collective variables are employed. The gain can be substantial when using massively parallel or GPU-based molecular dynamics software. Moreover, a theoretical framework to assess the sampling accuracy is introduced, which can be used to assess the choice of the integration time step in both single and multiple time step biased simulations.File | Dimensione | Formato | |
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