Calculation of Global, High-Dimensional Potential Energy Surface Fits in Canonical Decomposition Form Using Monte-Carlo Methods: Application to the Eigen Cation

2021 ◽  
pp. 73-86
Author(s):  
Markus Schröder ◽  
Hans-Dieter Meyer ◽  
Oriol Vendrell
Keyword(s):  
Monte Carlo ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Monte Carlo Methods ◽  
Energy Surface ◽  
Canonical Decomposition ◽  
High Dimensional

scholarly journals Theoretical Study of Rb2in HeN: Potential Energy Surface and Monte Carlo Simulations

2011 ◽  
Vol 115 (25) ◽  
pp. 6918-6926 ◽  
Author(s):  
Grégroire Guillon ◽  
Alexandre Zanchet ◽  
Markku Leino ◽  
Alexandra Viel ◽  
Robert E. Zillich
Keyword(s):  
Monte Carlo ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Monte Carlo Simulations ◽  
Energy Surface ◽  
Theoretical Study

scholarly journals Using principal component analysis for neural network high-dimensional potential energy surface

2020 ◽  
Vol 152 (23) ◽  
pp. 234103
Author(s):  
Bastien Casier ◽  
Stéphane Carniato ◽  
Tsveta Miteva ◽  
Nathalie Capron ◽  
Nicolas Sisourat
Keyword(s):  
Neural Network ◽  
Principal Component Analysis ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Principal Component ◽  
Component Analysis ◽  
High Dimensional

EXPLORING THE ENERGY LANDSCAPE

2005 ◽  
Vol 19 (15n17) ◽  
pp. 2877-2885 ◽  
Author(s):  
DAVID J. WALES
Keyword(s):  
Potential Energy ◽  
Potential Energy Surface ◽  
Rate Constants ◽  
Energy Surface ◽  
Energy Landscape ◽  
High Dimensional ◽  
Global Minima ◽  
Structure Dynamics ◽  
Recent Advances ◽  
Dimensional Object

Calculations of structure, dynamics and thermodynamics in molecular science all rely on the underlying potential energy surface (PES). Recent advances allow us to visualise this high-dimensional object in a compact fashion, locate global minima efficiently, and sample multistep pathways to obtain rate constants. These methods have been applied to a wide variety of systems, including clusters, glasses and biomolecules, and enable us to treat dynamics on the experimental timescale and beyond.

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