A self-learning algorithm for biased molecular dynamics.
A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias potential in terms of a patchwork of one-dimensional, locally vali...
Autors principals: | Tribello, G, Ceriotti, M, Parrinello, M |
---|---|
Format: | Journal article |
Idioma: | English |
Publicat: |
2010
|
Ítems similars
-
Using sketch-map coordinates to analyze and bias molecular dynamics simulations.
per: Tribello, G, et al.
Publicat: (2012) -
From the Cover: Simplifying the representation of complex free-energy landscapes using sketch-map.
per: Ceriotti, M, et al.
Publicat: (2011) -
Demonstrating the Transferability and the Descriptive Power of Sketch-Map
per: Ceriotti, M, et al.
Publicat: (2013) -
From the Cover: Simplifying the representation of complex free-energy landscapes using sketch-map.
per: Ceriotti, M, et al.
Publicat: (2011) -
Langevin equation with colored noise for constant-temperature molecular dynamics simulations.
per: Ceriotti, M, et al.
Publicat: (2009)