Investigating Phenomena at the Interface of Chemistry and Physics, One Atom at a Time.

Path integral MD

Developing classical molecular dynamics (MD) simulations that provide quantum expectation values for condensed phase systems.

ML and simulations

Applying powerful machine learning (ML) tools, such as artificial neural networks, to push the boundaries of molecular simulations.

Chemical Reactions

Using simulations to investigate fascinating problems, such as chemical reactions on water surfaces or stability of exotic phases of matter.

Read about our research

PIMD card

Artist rendition of Path integral configurations for two indistinguishable particles
(by Shiran Hirshberg)

Research spotlight: Path integral molecular dynamics including exchange effects.
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Being bosons or fermions is one of the most fundamental properties of quantum particles. PIMD simulations allow us to study thermodynamic properties of quantum systems using classical molecular dynamics - a great computational advantage. However, they completely neglect effects due to exchange. We have recently solved this important problem by developing a new PIMD method for bosons and fermions.

PIMD for bosons PIMD for fermions

‍Ynet - חוקרים חוזים את קיומו של "על-מוצק" במימן כבד
Researchers predict the existence of supersolid deuterium (in Hebrew)

שלושה שיודעים - ברק מסביר מהם על-מוצקים

החל מ- 1:02:50
Three who know podcast - Barak explains what supersolids are (in Hebrew)

Prediction of supersolid deuterium

We are hiring!

Several positions are available at all levels (Postdoc, PhD, MSc, undergratuate interns).
If you are interested in discovering how machine learning can improve molecular simulations, how to study quantum condensed phase systems using classical simulations, or how to apply these tools to exotic quantum materials or chemical reactions on water surfaces - get in touch!
To apply, please send your CV and a short description of your research interests to Barak.