Welcome‎ > ‎Courses‎ > ‎

Introduction to Statistical Physics from a Computational Perspective

Lesson 12: Stochastic optimisation: simulated annealing, genetic algorithms, pruning and enriching
Lesson 13: Disordered systems, spin glasses, neural networks
Lesson 14: Kinetic theory, Boltzmann Equation, Boltzmann H theorem
Lesson 15: Complexity
Lesson 16: Networks, small world

da considerare: Controllo e sincronizzazione; Boltzmann machines, Neural networks, branching processes (e funzioni generatrici), equazioni differenziali stocastiche (es. Ising. percolazione diretta), MArkov processes, master equation, ecc.