Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

MO: Fachverband Molekülphysik

MO 7: Machine Learning and Computational and Theoretical Molecular Physics

MO 7.2: Vortrag

Mittwoch, 8. März 2023, 11:30–11:45, F142

A machine learning full dimensional potential energy surface for AlF-AlF: lifetime of the intermediate complex — Weiqi Wang¹, •Xiangyue Liu¹, and Jesús Pérez-Ríos² — ¹Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany — ²Institute for Advanced Computational Science, Stony Brook University, Stony Brook, NY 11794-3800, USA

AlF is a promising candidate in the quest of finding the most efficient molecule for laser cooling. In this work, a full-dimensional potential energy surface of AlF-AlF dimer has been constructed by machine learning methods. In particular, we analyze the reliability and efficiency of different active learning schemes developed for this system. The potential energy surface has been employed in calculating the four-body complex lifetime relevant to the stability of molecules in the ultracold regime via molecular dynamics simulations.