Succinct resource covering topics starting from the basics of probability theory leading to applications in statistical physics, quantum theory, and complex systems
Starting from the very basics of probability theory leading up to applications and more advanced concepts, Random Processes in Physics covers the underlying theory and mathematics, illustrated through computer simulations to aid in seamless reader comprehension.
Following a linear presentation of concepts, the text is split into three parts: Fundamentals, Specific Probability, and Applications In and Beyond Physics. The first two parts provide material for a self-contained course on random processes (approximately a 24-hour lecture course). To aid in student information retention, each chapter includes a number of exercises with brief bottom-line answers.
Written by a highly qualified academic with significant experience in the field, Random Processes in Physics contains information on:
- General motivation, difficulties in dealing with probabilities and a number of basic examples, and general mathematical concepts underpinning probability theory
- Joint probabilities, Bayes theorem, how computers generate (pseudo-) random numbers, Central Limit Theorem, Gaussian distribution, and Poissonian distributions
- Levy flights, self-similarity, power law distributions (including applications), and extreme value statistics (e.g., Gumbel and Weibull distributions)
- Specific applications of random process modeling in physics and in selected adjacent disciplines, Markov chains, and Monte Carlo simulations
Random Processes in Physics is an ideal resource on the subject for first- and second-year undergraduate students in physics with an interest in the applications of modelling random processes, along with postgraduate research students working on statistical physics, quantum mechanics, or complex systems.
