Academic Year 2022/2023
- Docente: Armando Bazzani
- Credits: 6
- SSD: MAT/07
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
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Corso:
First cycle degree programme (L) in
Physics (cod. 9244)
Also valid for Second cycle degree programme (LM) in Computer Science (cod. 5898)
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from Sep 21, 2022 to Dec 23, 2022
Learning outcomes
Basic knowledge of physical and mathematical methods to develop dynamic and statistical model for the study of complex systems.
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.
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 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