Gaussian Mixture-Based Enhanced Sampling for Statics and Dynamics
Jayashrita Debnath, Michele Parrinello
Abstract
We introduce an enhanced sampling method that is based on constructing a model probability density from which a bias potential is derived. The model relies on the fact that in a physical system most of the configurations visited can be grouped into isolated metastable islands. With each island we associate a distribution that is fitted to a Gaussian mixture. The different distributions are linearly combined together with coefficients that are computed self-consistently. This leads to an integrated procedure for discovering new metastable states, exploring reaction pathways, computing free energy differences, and estimating reaction rates.
Topics & Concepts
Statistical physicsMetastabilityStaticsGaussianMolecular dynamicsSampling (signal processing)Mixture modelPhysicsProbability distributionProbability density functionGaussian processDynamics (music)MathematicsClassical mechanicsStatisticsQuantum mechanicsDetectorOpticsAcousticsProtein Structure and DynamicsSpectroscopy and Quantum Chemical StudiesGaussian Processes and Bayesian Inference