Statistical Mechanics 2
A.Y. 2019/2020
Learning objectives
The objective of the course is to present two sets of advanced topics of contemporary statistical mechanics
(i) a core of central arguments, which includes the relationships between statistical mechanics and probability theory, the understanding and use of mean-field methods, and the out-of-equilibrium dynamics
(ii) a set of modules that present varied models and fields of application (and can change year by year, even at the request of students)
(i) a core of central arguments, which includes the relationships between statistical mechanics and probability theory, the understanding and use of mean-field methods, and the out-of-equilibrium dynamics
(ii) a set of modules that present varied models and fields of application (and can change year by year, even at the request of students)
Expected learning outcomes
The student should ideally reach a solid and logical vision of statistical mechanics through the topics presented in the course, as well as the ability to frame these topics in a broader context.
In addition, the course aims to make students able to investigate new problems or subjects independently using books and articles
In addition, the course aims to make students able to investigate new problems or subjects independently using books and articles
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
The course content can be divided into
(i) a core of central arguments, which includes the relationships between statistical mechanics and probability theory, the understanding and use of mean-field methods, and the out-of-equilibrium dynamics and
(ii) a set of modules that present varied models and fields of application (and can change year by year, even at the request of students)
(i) a core of central arguments, which includes the relationships between statistical mechanics and probability theory, the understanding and use of mean-field methods, and the out-of-equilibrium dynamics and
(ii) a set of modules that present varied models and fields of application (and can change year by year, even at the request of students)
Prerequisites for admission
A previous knowledge of elementary Statistical Physics is useful.
Teaching methods
Frontal interactive lectures (it is recommended to attend)
Teaching Resources
See the slack space: statmech2.slack.com
The course is not based on any specific book, but the books by Peliti and Sethna can be a useful starting point for an independent study
L. Peliti Statistical Mechanics in a Nutshell (Princeton University Press, 2011)
J. Sethna Statistical Mechanics: Entropy, Order Parameters and Complexity (Oxford)
The course is not based on any specific book, but the books by Peliti and Sethna can be a useful starting point for an independent study
L. Peliti Statistical Mechanics in a Nutshell (Princeton University Press, 2011)
J. Sethna Statistical Mechanics: Entropy, Order Parameters and Complexity (Oxford)
Assessment methods and Criteria
The exam consists of an oral discussion that focuses on the topics covered in the course, addressing the ability of the student to elaborate a synthetic view of the subject and to explore independently a topic of choice.
FIS/02 - THEORETICAL PHYSICS, MATHEMATICAL MODELS AND METHODS - University credits: 6
Lessons: 42 hours
Professor:
Cosentino Lagomarsino Marco
Shifts:
-
Professor:
Cosentino Lagomarsino MarcoProfessor(s)
Reception:
By appointment, in-person and via Teams or other platforms.