CASUS Distinguished Lecture Series, Prof. Dr. Barak Hirshberg, Assistant Professor, School of Chemistry, Tel Aviv University, Israel

Barak Hirshberg has been an Assistant Professor at the School of Chemistry, Tel Aviv University since January 2021. Previously, he was a Rothschild postdoctoral fellow in the group of Prof. Michele Parrinello at ETH Zurich. He obtained his Ph.D. as an Adams Fellow of the Israel Academy of Sciences and Humanities with Prof. R. Benny Gerber at the Hebrew University of Jerusalem. Some of his recognitions include the Israel Chemical Society Prize for an Excellent Graduate Student and the Lise Meitner-Minerva Center Junior Award for an outstanding paper in computational quantum chemistry. Most recently, he was the inaugural awardee of the Rector Prize for Innovation and Creativity in Teaching, at Tel Aviv University.

The Hirshberg lab develops computer simulations for understanding the static and dynamic properties of quantum and classical condensed phase systems, focusing on molecular materials. The team designs algorithms to overcome the fundamental limitations of standard methods: extending them to much longer timescales, describing bosonic and fermionic exchange at finite temperatures, and simulating many-body quantum dynamics. Using these tools, it investigates phenomena such as quantum phase transitions, polymorphism in molecular crystals, and conformational dynamics in biomolecules.

Abstract of the talk// 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, and 2) including quantum statistics at a reasonable computational cost for studying quantum materials.

Barak will present recent work on overcoming these challenges. First, he 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. Barak and his team 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, he 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. Barak’s team employed resetting for enhanced sampling of molecular simulations for the first time. They showed that it accelerates long-timescale processes either as a standalone approach or combined with methods such as Metadynamics [3-4]. Most importantly, they can obtain the mean transition time without resetting, which is too long to be sampled directly, from simulations accelerated by resetting.

[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

Barak Hirshberg will be talking live in Görlitz. However, as the event is organized in a hybrid format that includes a videoconferencing tool by Zoom Inc., people interested in the topic have the chance to also join the talk remotely. Please ask for the login details via