Investigating of the structure of water using machine learning potentials and path integral molecular dynamics

Thomsen, B.  ; Shiga, Motoyuki   

We report our ongoing efforts to investigate how nuclear quantum effects (NQEs) influence the structure and dynamics properties of water. To model the NQEs we employ path integral molecular dynamics (PIMD), this does however require several ab initio calculations to be performed in each timestep to model the NQEs. In order to make the simulations more computationally affordable, we are currently working to describe the system using a machine learned potential (MLP). This MLP should be transferable across the isotopologues of water, and work across the phase diagram of water. We will here give an update on our ongoing work to improve the MLP description of water, and the results of PIMD simulations using this MLP.