This course introduces Monte Carlo simulation techniques, focusing on their applications in Statistical Physics. Students will explore simplified models of ferromagnetic materials, such as Ising and Potts models, gaining a foundational understanding of how Monte Carlo methods are applied across diverse scientific and technological fields, including biology, medicine, finance, condensed matter physics, and particle physics.
Key topics covered include:
Importance sampling principles and efficient algorithms.
Calculating estimators of observable quantities and their associated errors.
Analyzing autocorrelations in statistical samples generated by Markov chains.
From a physics perspective, the course emphasizes the study of critical properties in thermodynamic systems undergoing continuous phase transitions. Students will explore the concept of universality, where diverse microscopic systems exhibit similar macroscopic behavior. This concept has significant implications for various thermodynamic systems and quantum field theories in condensed matter and particle physics.
The course also covers:
Critical point approximation techniques.
Calculating critical quantities using finite-size scaling methods.
- Teacher: Κωνσταντίνος Αναγνωστόπουλος
ECTS : 5
Language : el