23762 - Physics of Complex Systems

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

Introduction to the Complex Systems Physics  and definition of the concept of complexity in science. The role of mathematical models in Physics: concept of predictivity. Construction of a model for a complex system and the role of nonlinear interactions. Introduction to the study of dynamical systems with applications to complex systems models. Methods for the study of stochastic dynamical systems. Introduction to statistical mechanics: concept of emergent property, critical state and phase transition. Analysis of models both from a theoretical and numerical point of view for the description of complex systems. Applications to physics, physical chemistry, biology, economics and social systems. Analysis of data distributions, comparison of exponential laws and power laws. Examples of study of a complex system model.

Readings/Bibliography

paper and materials provided during the course

G.Nicolis C.Nicolis FOUNDATIONS OF COMPLEX SYSTEMS
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 consists in areport on a project at the end of the course and it  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