
Course unit
STATISTICAL MECHANICS OF COMPLEX SYSTEMS
INP5070381, A.A. 2017/18
Information concerning the students who enrolled in A.Y. 2017/18
ECTS: details
Type 
ScientificDisciplinary Sector 
Credits allocated 
Core courses 
FIS/03 
Material Physics 
9.0 
Mode of delivery (when and how)
Period 
Second semester 
Year 
1st Year 
Teaching method 
frontal 
Organisation of didactics
Type of hours 
Credits 
Hours of teaching 
Hours of Individual study 
Shifts 
Lecture 
9.0 
72 
153.0 
No turn 
Start of activities 
26/02/2018 
End of activities 
01/06/2018 
Examination board
Board 
From 
To 
Members of the board 
2 2016 
01/10/2016 
15/03/2018 
MARITAN
AMOS
(Presidente)
SENO
FLAVIO
(Membro Effettivo)
TROVATO
ANTONIO
(Supplente)

Prerequisites:

Good knoledge of mathematical analysis, calculus and basic physics. 
Target skills and knowledge:

Objective
Introduce the students to topics in statistical mechanics of complex systems.
Outcomes
A student who has met the objectives of the course will have a practical knowledge of :
• Models of statistical mechanics of natural systems
• Complex networks. 
Examination methods:

Final examination based on: Written and oral examination. 
Assessment criteria:

Critical knowledge of the course topics.Ability to present the studied material. Discussion of the student project. 
Course unit contents:

1. Equilibrium statistical mechanics, the principle of maximum
entropy, statistical ensemble, derivation of thermodynamics, paradigmatic models of statistical mechanics, mean field theory, critical phenomena and scaling.
2. Fractal geometry with applications to the natural forms of many systems (for example transportation networks, river basins).
3. Scaling theory and its use in physics, ecology, biology.
4. Nonequilibrium statistical mechanics, Brownian motion/diffusion, Markov processes, Langevin equation and the FokkerPlanck, linear response theory. Applications to biology, ecology and human mobility / traffic.
5. Graph theory with application to architecture ecological, biological and food trade networks. 
Planned learning activities and teaching methods:

Lecture supported by tutorial, assignment, analytical and numerical problems 
Additional notes about suggested reading:

Lecture notes and reference books will be given by the lecturer. 
Textbooks (and optional supplementary readings) 

J. P. Sethna, Entropy, Order Parameters and Complexity. : Oxford, 2015.


