Machine learningStochastic Method

Quantum Monte Carlo

Quantum Monte Carlo (QMC) is a stochastic computational method for computing ground state properties of quantum many-body systems. Combining classical Monte Carlo sampling with quantum mechanics, QMC approaches are among the most accurate methods available for electronic structure and condensed matter physics, achieving sub-percent accuracy for many systems.

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Metropolis, N., Rosenbluth, A. W., et al. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087–1092. DOI: 10.1063/1.1699114
  2. Reynolds, P. J., Tobochnik, J., Gould, H. (1990). Diffusion quantum Monte Carlo. Computers in Physics, 4, 662–668. DOI: 10.1063/1.4822927
  3. Needs, R. J., et al. (2020). Variational and diffusion quantum Monte Carlo calculations with the CASINO code. The Journal of Chemical Physics, 152, 154106. DOI: 10.1063/1.5144445

Related methods

Referenced by

ScholarGateQuantum Monte Carlo (Quantum Monte Carlo (QMC)). Retrieved 2026-06-04 from https://scholargate.app/en/quantum-computing/quantum-monte-carlo