ABSTRACT
Monte Carlo methods are a class of computational algorithms that estimate a result based on repeated stochastic sampling. The earliest documented instance of such a method dates back to 1777, when Georges-Louis Leclerc, Comte de Buffon, performed an experiment consisting in dropping a needle at random onto a plane marked with equally spaced parallel lines to infer the probability of the needle lying across one of the lines, the latter probability being 129
129actually directly related to the value of pi. Inspired by the famous casino of Monte Carlo in Monaco, the name of the methods was then coined in the 1940s by physicists working on nuclear weapon projects at the Los Alamos National Laboratory.
