Path Integral Monte Carlo

By John Shumway1, Matthew Gilbert2

1. Arizona State University 2. University of Texas at Austin

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Version 2013.09LTS-0w - published on 17 Mar 2015

doi:10.4231/D3T43J39D cite this

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Path integral Monte Carlo (PIMC) simulates particles (often electrons and ions) by directly sampling the canonical partition function. In the path integral formulation of quantum statistical mechanics developed by Richard Feynman, particles get represented by closed imaginary-time trajectories of length h/kT. PIMC simulations are able to compute total energies, correlation functions, charge distribution, and linear response functions for thermal equilibrium. As in many quantum Monte Carlo methods, PIMC has efficient scaling with system size, often order N or N2. Our application, pi-qmc or app-pimc, is well suited for modeling conduction electrons in quantum dots, quantum wires, and quantum wells. We have also tested it for ab initio calculations, but at this point only hydrogen and helium atoms work well. The app-pimc tool is a low-level wrapper for our application that allows the user to input a simulation description in XML, run the simulation in 1, 2, or 3 dimensions, and view results of scalar estimators. While this is an expert interface, we provide demo input files for quick simulations of a free particle, simple harmonic oscillator, and a hydrogen atom. The code is open source, so users have the option of installing a local version of the program on their machines if that better suites their research.

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pi: Open-Source Path Integral QMC

Open source path integral simulation program developed by the Shumway research group.

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Work supported by NSF Grants OCI 1148502 and DMR 0239819, DARPA/ONR N00014-01-1-1062, and SRC-NRI SWAN.


Cite this work

Researchers should cite this work as follows:

  • John Shumway; Matthew Gilbert (2015), "Path Integral Monte Carlo," (DOI: 10.4231/D3T43J39D).

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  1. nanoelectronics
  2. quantum Monte Carlo
  3. quantum mechanics
  4. quantum transport
  5. quantum dots
  6. nanoelectronics
  7. quantum Monte Carlo
  8. quantum mechanics
  9. quantum transport
  10. quantum dots
  11. nanoelectronics
  12. quantum Monte Carlo
  13. quantum mechanics
  14. quantum transport
  15. quantum dots
  16. open source tool