Statistical Mechanics of Complex Systems

Period: Second semester

Course unit contents: The program can be summarized as follows

• Statistical mechanics and Entropy
• Ising model
• Variational principles in statistical mechanics
• Complex networks
• Principle of maximum entropy and inference
• Diffusion Processes and stochastic dynamics
• Montecarlo simulations
• Dynamics of and on networks
• Population dynamics with applications to ecosystems
• Percolation on networks.
• Neural networks

Planned learning activities and teaching methods: The course is organized in lectures whose contents are presented on the blackboard, sometimes with the help of images, diagrams and videos. The teaching is interactive, with questions and presentation of case studies, in order to promote discussion and critical thinking.