Machine learning and excited-state molecular dynamics

摘要: Machine learning is employed at an increasing rate in the research field of quantum chemistry. While majority approaches target investigation chemical systems their electronic ground state, inclusion light into processes leads to electronically excited states and gives rise several new challenges. Here, we survey recent advances for excited-state dynamics based on machine learning. In doing so, highlight successes, pitfalls, challenges future avenues light-induced molecular processes.