Active Learning of Boltzmann Samplers and Potential Energies with Quantum Mechanical Accuracy

Extracting consistent statistics between relevant free energy minima of a molecular system is essential for physics, chemistry, and biology. Molecular dynamics (MD) simulations can aid in this task but are computationally expensive, especially for systems that require quantum accuracy. To overcome t...

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Veröffentlicht in:	Journal of chemical theory and computation 2024-10, Vol.20 (20), p.8833-8843
Hauptverfasser:	Molina-Taborda, Ana, Cossio, Pilar, Lopez-Acevedo, Olga, Gabrié, Marylou
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Adaptive sampling Boltzmann distribution Energy distribution Free energy Isomerization Machine learning Markov chains Molecular dynamics Nanoclusters Normalizing (statistics) Quantum mechanics Samplers Statistical Mechanics
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