First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
Course unit
SCP7081659, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course Second cycle degree in
SC2382, Degree course structure A.Y. 2017/18, A.Y. 2018/19
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Degree course track PHYSICS OF MATTER [002PD]
Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination STATISTICAL MECHANICS
Website of the academic structure
Department of reference Department of Physics and Astronomy
E-Learning website
Mandatory attendance No
Language of instruction English
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge ENZO ORLANDINI FIS/03
Other lecturers FELIX RITORT

Course unit code Course unit name Teacher in charge Degree course code

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses FIS/02 Theoretical Physics, Mathematical Models and Methods 6.0

Course unit organization
Period First semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Lecture 6.0 48 102.0 No turn

Start of activities 01/10/2018
End of activities 18/01/2019

Examination board
Board From To Members of the board
2 STATISTICAL MECHANICS 01/10/2018 30/11/2019 ORLANDINI ENZO (Presidente)
BALDOVIN FULVIO (Membro Effettivo)
1 STATISTICAL MECHANICS 01/10/2017 30/11/2018 ORLANDINI ENZO (Presidente)
BALDOVIN FULVIO (Membro Effettivo)

Prerequisites: Statistical Mechanics (course given at the third year of the laurea triennale)
Target skills and knowledge: After completing the course the student should be able to understand and explain the basic concepts and the use of advanced techniques in statistical mechanics.
In particular the student should
1) give an account of the relevant quantities used to describe macroscopic systems, thermodynamic potentials and ensemble.
2) Understand the use of partition functions and their relation with thermodynamics
3) Explain the concept of phase transitions in simple models as well as the physics at or near critical points.
4) Understand the role of dimension and range of interaction in phase transitions
5) Apply the theory of scaling and the renormalisation group to simple systems

6) Understand the strength and limitation of the models
7) Show an analytic ability to solve problems relevant to statistical physics
Examination methods: The verification of the acquired knowledge takes place through a common written test with 1-2 exercises to be solved analytically and 1-2 open questions on basic concepts. In this way we should be able to test the knowledge, the scientific vocabulary, the ability to synthesis and critical discussion acquired during the course.The second part of the exam will be oral and will be based on a discussion on the various topics discussed in class.
Assessment criteria: The criteria used to verify the knowledge and skills acquired are:
1) understanding of the topics covered;
2) critical ability to connect the acquired knowledge;
3) completeness of the acquired knowledge;
4) synthesis ability;
5) understanding of the terminology used
6) ability to use the analytical methodologies and techniques illustrated during the course to solve or at least set problems where statistical mechanics plays an important role.
Course unit contents: In short the contents of the program can be summarised as follows:
Thermodynamics of phase transitions.
Critical points, order parameters and critical exponents. Phase transitions and spontaneous symmetry breaking.
Analytical tools to solve spins model in 1D, transfer matrix formalisms.
Mean field theories.
Ginzburg Landau theory.
Ginzburg criterium and upper critical dimension. Scaling theory and Kadanoff block spin argument.
Renormalisation group in real space. Universality.

Please note that some topics may vary
Spontaneous symmetry breaking for continuous symmetry. Goldstone's theorem.
Planned learning activities and teaching methods: The course is organized in lectures whose contents are presented on the blackboard, sometimes with the help of images, diagrams and videos. The teaching is interactive, with questions and presentation of case studies, forpromote discussion and critical reflection in the classroom.
Additional notes about suggested reading: All the teaching material used for lectures (blackboard lessons, case study articles, review of the content of the recommended texts) is made available to students in pdf format on the e-learning platform: https: // elearning.
Textbooks (and optional supplementary readings)
  • K. Huang, Meccanica Statistica. --: Zanichelli, --. Cerca nel catalogo
  • L. Peliti, Statistical Mechanics in a Nutshell. --: Princeton, --. Cerca nel catalogo
  • J. Yeomans, Statistical mechanics of Phase transitions. Oxford: Oxford University Press, 1992. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Questioning
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • Latex

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