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• W2983707099 abstract "Atomistic modelling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an appropriately-chosen set of collective variables can significantly accelerate the exploration of phase space, albeit at the price of distorting the distribution of microstates. Efficient re-weighting to recover the unbiased distribution can be nontrivial when employing adaptive sampling techniques such as Metadynamics, Variationally Enhanced Sampling or Parallel Bias Metadynamics, in which the system evolves in a quasi-equilibrium manner under a time-dependent bias. We introduce an iterative unbiasing scheme that makes efficient use of all the trajectory data, and that does not require the distribution to be evaluated on a grid. The method can thus be used even when the bias has a high dimensionality. We benchmark this approach against some of the existing schemes, on models systems with different complexities and dimensionalities." @default.
• W2983707099 created "2019-11-22" @default.
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• W2983707099 date "2019-11-04" @default.
• W2983707099 modified "2023-10-01" @default.
• W2983707099 title "Iterative unbiasing of quasi-equilibrium sampling" @default.
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• W2983707099 hasPublicationYear "2019" @default.
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