Statistical Physics

Instance: 2022/2023 - 1S

Cycles of Study/Courses

Teaching language

Objectives

To get familiar with the ideas and methods of statistical physics. To introduce the fundamental results of classical and quantum statistical physics of systems in equilibrium. To discuss some applications of statistical physics to classical and quantum systems.

Learning outcomes and competences

To be able to solve problems by means of a statistical approach and to establish the connection with thermodynamics. To perform some simple numerical simulations.

Working method

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Some basic knowledge of Mechanics and Thermal Physics.

Program

Notions of the Theory of Probability and Statistics. Binomial, Gaussian and Poisson distributions. Central limit theorem. Numerical simulation of random processes. Random walk and the diffusion equation. Ideas based on Statistical Physics. Description and enumeration of states. Statistical ensemble. Classical systems. Dynamics in phase space. Ergodic hypothesis. Classical Statistical Physics. Microcanonical, canonical and macrocanonical distributions. Monte-Carlo Method in Statistical Physics. Simple and importance sampling. Metropolis method. Quantum statistics. Bose-Einstein and Fermi-Dirac statistics. Classical limit. Perfect Bose gas. Perfect Fermi gas. Applications. Bose-Einstein condensation, conduction electrons in metals, specific heat of solids, star equilibrium and evolution.

Mandatory literature

Complementary Bibliography

Teaching methods and learning activities

Practical classes to solve analytical and computacional problems.

Software

keywords

Evaluation Type

Assessment Components

Amount of time allocated to each course unit

Eligibility for exams

Students should not exceed 4 absences in problem classes.

Calculation formula of final grade

The student must opt ​​for an assessment with a continuous component and 
an exam or just to take an exam.

In the assessment with a continuous component, the student must do three
homework during the semester. The continuous component is worth 30% of 
the final grade and the exam 70%.

In the evaluation without continuous component, the exam is worth 100%.

Examinations or Special Assignments

Internship work/project

Special assessment (TE, DA, ...)

Classification improvement

Observations