Machine learningMonte Carlo Method

Path Integral Monte Carlo

Path 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.

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Sources

  1. Feynman, R. P. (1948). Space-time approach to non-relativistic quantum mechanics. Reviews of Modern Physics, 20, 367–387. DOI: 10.1103/RevModPhys.20.367
  2. Ceperley, D. M. (1995). Path integrals in the theory of condensed helium. Reviews of Modern Physics, 67, 279–355. DOI: 10.1103/RevModPhys.67.279
  3. Trofimov, D., et al. (2020). Practical path integral Monte Carlo. Annual Review of Computational Physics, 2, 165–190. link

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Referenced by

ScholarGatePath Integral Monte Carlo (Path Integral Monte Carlo (PIMC)). Retrieved 2026-06-04 from https://scholargate.app/en/quantum-computing/path-integral-monte-carlo