Department of Chemistry Seminar - Anatole von Lilienfeld

The Department of Chemistry presents: Anatole von Lilienfeld

University of Toronto

Host: Graeme Henkelman

Title: Quantum machine learning in chemical space

Location: WEL 2.122

Refreshments served at 3:15pm

Many of the most relevant observables of matter depend explicitly on atomistic and electronic structure, rendering physics-based approaches to chemistry and materials necessary. Unfortunately, due to the combinatorial scaling of the number of chemicals and potential reaction settings, gaining a holistic and rigorous understanding through exhaustive quantum and statistical mechanics-based sampling is prohibitive --- even when using high-performance computers. Accounting for explicit and implicit dependencies and correlations, however, will not only deepen our fundamental understanding but also benefit exploration campaigns (computational and experimental). I will discuss recently gained insights from my lab elucidating such relationships thanks to alchemical perturbation density functional theory and supervised machine learning.