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Path Integral Monte Carlo×Tæthedsfunktionalteori×
FagområdeKvanteberegningKvanteberegning
FamilieMachine learningMachine learning
Oprindelsesår19481965
OphavspersonRichard FeynmanWalter Kohn
TypeStochastic simulationElectronic structure method
Oprindelig kildeFeynman, R. P. (1948). Space-time approach to non-relativistic quantum mechanics. Reviews of Modern Physics, 20, 367–387. DOI ↗Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138. DOI ↗
AliasserPIMC, Feynman path integralDFT, Kohn-Sham equations
Relaterede34
ResuméPath Integral Monte Carlo (PIMC) is a computational method for calculating thermodynamic and structural properties of quantum systems using Feynman's path integral formulation. Developed rigorously by David Ceperley and colleagues in the 1990s, PIMC treats quantum particles as classical polymers in a higher-dimensional space, enabling efficient Monte Carlo sampling of quantum statistics.Density Functional Theory (DFT) is a computational method for determining the properties of materials and molecules by modeling the ground state electron density. Developed by Walter Kohn and Lu Jeu Sham in the 1960s, DFT reduces the complexity of quantum chemistry from tracking individual electron coordinates to optimizing the total electron density, enabling efficient simulations of large molecular and condensed-matter systems.
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ScholarGateSammenlign metoder: Path Integral Monte Carlo · Density Functional Theory. Hentet 2026-06-18 fra https://scholargate.app/da/compare