Interpolating many-body wave functions for accelerated molecular dynamics on the near-exact electronic surface

• URL: http://arxiv.org/abs/2402.11097v2
• Date: Tue, 13 Aug 2024 21:57:20 GMT
• Title: Interpolating many-body wave functions for accelerated molecular dynamics on the near-exact electronic surface
• Authors: Yannic Rath, George H. Booth,
• Abstract summary: We develop a scheme for the correlated many-electron state through the space of atomic configurations. We demonstrate provable convergence to near-exact potential energy surfaces for subsequent dynamics. We combine this with modern electronic structure approaches to systematically resolve molecular dynamics trajectories.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: While there have been many developments in computational probes of both strongly-correlated molecular systems and machine-learning accelerated molecular dynamics, there remains a significant gap in capabilities in simulating accurate non-local electronic structure over timescales on which atoms move. We develop an approach to bridge these fields with a practical interpolation scheme for the correlated many-electron state through the space of atomic configurations, whilst avoiding the exponential complexity of these underlying electronic states. With a small number of accurate correlated wave functions as a training set, we demonstrate provable convergence to near-exact potential energy surfaces for subsequent dynamics with propagation of a valid many-body wave function and inference of its variational energy whilst retaining a mean-field computational scaling. This represents a profoundly different paradigm to the direct interpolation of potential energy surfaces in established machine-learning approaches. We combine this with modern electronic structure approaches to systematically resolve molecular dynamics trajectories and converge thermodynamic quantities with a high-throughput of several million interpolated wave functions with explicit validation of their accuracy from only a few numerically exact quantum chemical calculations. We also highlight the comparison to traditional machine-learned potentials or dynamics on mean-field surfaces.

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