Computational Nanoscience, Lecture 21: Quantum Monte Carlo, part II
- Computational Nanoscience, Lecture 8: Monte Carlo Simulation Part II
- Computational Nanoscience, Lecture 7: Monte Carlo Simulation Part I
- Computational Nanoscience, Lecture 20: Quantum Monte Carlo, part I
- The basics of quantum Monte Carlo
- Monte Carlo Method and Its Applications
- ECE 656 Lecture 31: Monte Carlo Simulation
- Particle Based Monte Carlo Simulator for Bulk Semiconductors
- Generalized Monte Carlo Presentation
This is our second lecture in a series on Quantum Monte Carlo methods. We describe the Diffusion Monte Carlo approach here, in which the approximation to the solution is not restricted by choice of a functional form for the wavefunction. The DMC approach is explained, and the fixed node approximation is described as well. We conclude with a few examples demonstrating the application of VMC and DMC to methane and ethane.
University of California, Berkeley
Researchers should cite this work as follows:
Jeffrey C Grossman; Elif Ertekin (2008), "Computational Nanoscience, Lecture 21: Quantum Monte Carlo, part II," https://nanohub.org/resources/4566.