Molecular dynamics simulations are powerful, providing microscopic insight into condensed-phase chemical processes.
However, two outstanding challenges of the standard algorithms are:

1) Extending simulations to longer timescales, allowing the description of phenomena such as the nucleation and growth of crystals.
2) Including quantum statistics at a reasonable computational cost for studying quantum materials.

I will present our recent work on overcoming these challenges. First, I will introduce a method for bosonic path integral molecular dynamics simulations (PIMD). While widely used in chemistry and physics, PIMD assumes that the particles are distinguishable, neglecting exchange statistics. The main difficulty is enumerating all particle permutations, whose number grows exponentially with system size. We developed a recursive algorithm that reduced the scaling from exponential to quadratic, allowing the first applications of PIMD to bosonic systems composed of thousands of particles [1-2].

Secondly, I will present a method to expedite MD simulations to longer timescales using stochastic resetting. Processes such as crystal nucleation and growth often display broad transition time distributions in which rare events have a non-negligible probability. Stochastic resetting, i.e., restarting simulations at random times, was recently shown to expedite processes obeying such distributions. We employed resetting for enhanced sampling of molecular simulations for the first time. We showed that it accelerates long-timescale processes either as a standalone approach or combined with methods such as Metadynamics [3-4]. Most importantly, we can obtain the mean transition time without resetting, which is too long to be sampled directly, from simulations accelerated by resetting.

References:
[1] B Hirshberg, V Rizzi, M Parrinello, Proceedings of the National Academy of Sciences, 2019, 116 (43), 21445-21449
[2] YMY Feldman, B Hirshberg, The Journal of Chemical Physics, 2023, 159 (15), 154107
[3] O Blumer, S Reuveni, B Hirshberg, The Journal of Physical Chemistry Letters, 2022, 13 (48), 11230-11236
[4] O Blumer, S Reuveni, B Hirshberg, Nature Communications, 2024, 15 (1), 240