Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Graph
Search

Course

PHYS-316: Statistical physics II

Summary

Introduction à la théorie des transitions de phase

Lectures

Instructors

Official source

https://edu.epfl.ch/coursebook/en/statistical-physics-ii-PHYS-316

Moodle Page

http://go.epfl.ch/PHYS-316

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Summary

Introduction à la théorie des transitions de phase

Lectures

Instructors

Official source

https://edu.epfl.ch/coursebook/en/statistical-physics-ii-PHYS-316

Moodle Page

http://go.epfl.ch/PHYS-316

About this result

Ontological neighbourhood

Physics

Condensed matter physics: Phase transitions

Mathematics

Algebra: Linear algebra

Statistics

Statistical inference: Mathematical statistics

Lectures in this course (27)

Phase Transitions

Explores phase transitions, critical points, opalescence, and metastability in substances.

Phase Transition in Ising Model

Explores phase transitions in the Ising model, discussing equilibrium states, magnetization, and critical points.

Spatial Response and Convolution

Covers the spatial response of systems, including the calculation of the center of mass and convolution.

Phase Transitions

Explores phase transitions in two-dimensional systems and the critical behavior near transition points.

Ising Model: 2D High Temperature Expansion

Explores the high-temperature expansion of the Ising model in 2D square lattice.

Related courses (30)

PHYS-739: Conformal Field theory and Gravity

This course is an introduction to holography, the modern approach to quantum gravity. ...

PHYS-467: Machine learning for physicists

Machine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised. ...

PHYS-432: Quantum field theory II

The goal of the course is to introduce relativistic quantum field theory as the conceptual and mathematical framework describing fundamental interactions such as Quantum Electrodynamics. ...

PHYS-441: Statistical physics of biomacromolecules

Biological macromolecules such as DNA, RNA, proteins and cytoskeletal filaments are polymers. As such, they share a set of properties that are common to any polymer, which are the focus of this course. Details about the protein folding problem will be cove ...

PHYS-512: Statistical physics of computation

The students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and machine learning. ...