23762 - Physics of Complex Systems

Course Unit Page

Academic Year 2022/2023

Learning outcomes

Basic knowledge of physical and mathematical methods to develop dynamic and statistical model for the study of complex systems. Basic knowledge of graphical methods 2D and 3D used to illustrate the results.

Course contents

Complex system definition. Role of non-linear interactions.Simple theoretical and numerical models for complex systems.Examples from Physics, economy and biology.Data distribution: comparison between exponential and power laws.Agent, neural network and cellular automata models.

Introduction to the study of dynamical systems with applications to complex systems models. Methods for the study of stochastic dynamical systems and their applications to a statistical mechanics approach. Concept of emergent property, critical state and phase transition. Use of simulations for the study of mathematical physical models.


paper and materials provided during the course

Nonlinear Dynamics, Statistical Physics, Information
and Prediction World Scientific 2007

Numerical Recipes, W.H.Press et al, Cambridge University Press

Teaching methods

lessons, seminar and home works.

Assessment methods

The final exam and/or the project report at the end of the course aims to assess the achievement of learning objectives:

- To know the methodologies of the discipline in particular on data analysis, on numerical simulations and on solution visualization.

- To understand the characteristics of the various physical and social systems to which the methodologies discussed can be applied.

Teaching tools

personal PC. videoprojector, internet

Office hours

See the website of Armando Bazzani