A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential
Chen Qu, Qi Yu, Riccardo Conte, Paul L. Houston, Apurba Nandi, Joel M. Bomwan
Abstract
In this paper we proposed a Δ-machine learning approach to correct general many-body force fields. We illustrate this approach by adding a 4-body correction to the MB-pol water potential to bring it to a higher level of accuracy.
Topics & Concepts
Water bodyForce field (fiction)Computer scienceArtificial intelligenceMachine learningEngineeringGeotechnical engineeringMachine Learning in Materials ScienceProtein Structure and DynamicsQuantum many-body systems