The purpose of this book is twofold: first, it sets out to equip the
reader with a sound understanding of the foundations of probability
theory and stochastic processes, offering step-by-step guidance from
basic probability theory to advanced topics, such as stochastic
differential equations, which typically are presented in textbooks that
require a very strong mathematical background. Second, while leading the
reader on this journey, it aims to impart the knowledge needed in order
to develop algorithms that simulate realistic physical systems.
Connections with several fields of pure and applied physics, from
quantum mechanics to econophysics, are provided. Furthermore, the
inclusion of fully solved exercises will enable the reader to learn
quickly and to explore topics not covered in the main text. The book
will appeal especially to graduate students wishing to learn how to
simulate physical systems and to deepen their knowledge of the
mathematical framework, which has very deep connections with modern
quantum field theory.