Simulations and Monte Carlo methods

Monte Carlo simulation methods can be seen as approximation methods, even if they are approximations in the statistical sense of the term. There is no absolute consensus on a precise definition of what a Monte Carlo technique is, but the most common description is that such methods are characterized by the use of chance to solve problems centered on a calculation. They are generally applicable to numerical problems, or to problems of a probabilistic nature.

In terms of applications, these methods are indispensable today in fields as varied and diverse as finance, the development of new electronic microcomponents, seismology, telecommunications, engineering or physics, but also in biology, social sciences, etc. For example, in chemistry, physics or even biology, many problems require the analysis of the dynamic properties of such a large number of objects (atomic particles, atoms, molecules or macromolecules), that this can only be done using Monte Carlo-type techniques.