<i>Ab initio</i> molecular dynamics (AIMD) simulations employing density functional theory (DFT) and plane waves are routinely carried out using density functionals at the level of generalized gradient approximation (GGA). Hybrid density functional based AIMD simulations are known to offer a more accurate description of structural and dynamic properties than the GGA functionals. However, these calculations are at least two orders of magnitude more expensive than those using GGA functionals, which limits the use of hybrid functionals in plane wave based AIMD. In this work, we propose a strategy that combines the adaptively compressed exchange (ACE) operator formulation and the multiple time step integration scheme to reduce the computational cost by an order of magnitude. Systematic introduction of localized orbitals for the construction of the ACE operator further reduces the computational cost. Implementation of these methods with a task-group based parallelization in the CPMD program package allows us to take advantage of the large number of compute cores available on modern high-performance computing platforms. Benchmark results indicate that for model systems with 32, 64 and 128 water molecules, computational overhead for doing hybrid density functional based AIMD is only 2-4 times more expensive than with GGA functional. To demonstrate the applicability, computationally intensive free energy computations at the level of hybrid density functional theory were performed to investigate proton transfer reactions.

Improving the scaling and performance of hybrid functional and plane wave based <i>ab initio</i> molecular dynamics

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Improving the scaling and performance of hybrid functional and plane wave based ab initio molecular dynamics