2017/03/31 by James McCarty, J. McCarty, Michele Parrinello · 2 citations
Chemistry · Mathematics · Physics and Astronomy · #Artificial intelligence #Chemistry #Complex system #Component (thermodynamics) #Computational chemistry #Computer science #Convergence (economics) #Energy landscape #Mathematical optimization #Mathematics #Metadynamics #Molecular dynamics #Physics #Power (physics) #Quantum chaos and dynamical systems #Quantum mechanics #Selection (genetic algorithm) #Statistical Mechanics and Entropy #Statistical physics #Theoretical and Computational Physics #cond-mat.stat-mech
paper · pdf · doi:10.1063/1.4998598
published as The Journal of Chemical Physics, Vol.147, Issue 20, 2017 · 7 pages, 4 figures
openalex publication_date 2017/11/28 · arxiv created 2017/12/07 · arxiv updated 2017/12/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
In this paper, we combine two powerful computational techniques, well-tempered metadynamics and time-lagged independent component analysis. The aim is to develop a new tool for studying rare events and exploring complex free energy landscapes. Metadynamics is a well-established and widely used enhanced sampling method whose efficiency depends on an appropriate choice of collective variables. Often the initial choice is not optimal leading to slow convergence. However by analyzing the dynamics generated in one such run with a time-lagged independent component analysis and the techniques recently developed in the area of conformational dynamics, we obtain much more efficient collective variables that are also better capable of illuminating the physics of the system. We demonstrate the power of this approach in two paradigmatic examples.