This lecture discusses basic principles of Monte-Carlo methods, a class of computational algorithms. A simple example of estimating value of pi is discussed. Monte-carlo techniques are widely used in the areas of modern physics, nuclear simulation, astro-physics and many other areas of science and engineering where direct computation or analytical solutions are impossible or too difficult to obtain. The name comes from a top secret nuclear project during world war II. A scientist in the project group suggested a name Monte-Carlo which is a casino in Monaco. Monte-Carlo methods make use of probability and probability distributions play a major role in the outcome of the algorithm.
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