Efficient Training and Implementation of Gaussian Process PotentialsTools Broad, Jack W. (2022) Efficient Training and Implementation of Gaussian Process Potentials. PhD thesis, University of Nottingham.
AbstractMolecular simulations are a powerful tool for translating information about the intermolecular interactions within a system to thermophysical properties via statistical mechanics. However, the accuracy of any simulation is limited by the potentials that model the microscopic interactions. Most first principles methods are too computationally expensive for use at every timestep or cycle of a simulation, which require typically thousands of energy evaluations. Meanwhile, cheaper semiempirical potentials give rise to only qualitatively accurate simulations. Consequently, methods for efficient first principles predictions in simulations are of interest.
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