Markov chain
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In probability theory and statistics, a Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability of each event depends only on the state
Russian mathematician Andrey Markov
Wiener process
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In mathematics, the Wiener process is a real-valued continuous-time stochastic process named after Norbert Wiener. It is one of the best known Lévy processes. It occurs frequently in pure and applied
Markov chain
…of these processes were studied hundreds of years earlier in the context of independent variables. Two important examples of Markov processes are the Wiener process, also known as the Brownian motion process, and the Poisson process, which are considered the most important and central stochastic processes in the…
The generator of Brownian motion on Riemannian manifolds is 1⁄2 times the Laplace–Beltrami operator. The image above shows Brownian motion on the surface of a 2-sphere.