Monte Carlo method
Método de Montecarlo
- Date
- 1946 · confidence high
- Place
- Los Alamos, New Mexico, United States
- Credited to
- Stanislaw Ulam, John von Neumann and Nicholas Metropolis
- People
- 👤 Enrico Fermi1901–1954👤 John von Neumann1903–1957👤 Stanisław Ulam1909–1984
- Field
- Knowledge & symbols
What was discovered
Solving deterministic or probabilistic problems through massive random sampling on a computer, devised for neutron diffusion. The first major scientific use of the computer and the origin of stochastic simulation.
The name alludes to the Monte Carlo casino, where an uncle of Ulam's used to gamble.
What it led to
- computational simulation
- the Metropolis-Hastings algorithm
- Bayesian MCMC
- high-dimensional integration
- Simulation of nuclear weapons, reactors and particle physics
- Quantitative finance and derivatives pricing
- Modern Bayesian inference (MCMC) and probabilistic AI
Built on
- Probability theory (problem of points)1654
- Kolmogorov axioms of probability1933
- Atomic bomb1945
- ENIAC1945
- Buffon's needle (1777)
- Kolmogorov probability
Made possible
- Fermi–Pasta–Ulam–Tsingou problem1953
- Metropolis–Hastings algorithm1953 (Metropolis) / 1970 (generalización de Hastings)
- design of nuclear reactors and weapons
- financial risk management
- ray-tracing rendering
- reactor simulation
- financial models
- MCMC methods