Fast and accurate nonadiabatic molecular dynamics enabled through variational interpolation of correlated electron wavefunctions
Faraday Discussions(2024)
摘要
We build on the concept of eigenvector continuation to develop an efficient
multi-state method for the rigorous and smooth interpolation of a small
training set of many-body wavefunctions through chemical space at mean-field
cost. The inferred states are represented as variationally optimal linear
combinations of the training states transferred between the many-body basis of
different nuclear geometries. We show that analytic multi-state forces and
nonadiabatic couplings from the model enable application to nonadiabatic
molecular dynamics, developing an active learning scheme to ensure a compact
and systematically improvable training set. This culminates in application to
the nonadiabatic molecular dynamics of a photoexcited 28-atom hydrogen chain,
with surprising complexity in the resulting nuclear motion. With just 22 DMRG
calculations of training states from the low-energy correlated electronic
structure at different geometries, we infer the multi-state energies, forces
and nonadiabatic coupling vectors at 12,000 geometries with provable
convergence to high accuracy along an ensemble of molecular trajectories, which
would not be feasible with a brute force approach. This opens up a route to
bridge the timescales between accurate single-point correlated electronic
structure methods and timescales of relevance for photo-induced molecular
dynamics.
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