Statistical Physics

Code:

FIS3008

Acronym:

FIS3008

Keywords
Classification	Keyword
OFICIAL	Physics

Instance: 2021/2022 - 1S

Active?	Yes
Responsible unit:	Department of Physics and Astronomy
Course/CS Responsible:	Bachelor in Physics

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:F	53	Official Study Plan	3	-	6	49	162

Teaching language

Portuguese

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

Presencial

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

Kardar Mehran; Statistical physics of particles. ISBN: 978-0-521-87342-0
Reif F. (Frederick); Fundamentals of statistical and thermal physics. ISBN: 0-07-051800-9
T. Fliesbach ; Curso de Física Estatística
S. Salinas ; Introdução à Física Estatística
E. Lage ; Física Estatística

Complementary Bibliography

Huang Kerson; Statistical mechanics. ISBN: 0-471-81518-7
Harvey Gould; Thermal and statistical physics simulations. ISBN: 0-471-54886-3

Teaching methods and learning activities

Practical classes to solve analytical and computacional problems.

Software

Python

keywords

Physical sciences

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	70,00
Trabalho escrito	30,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Frequência das aulas	49,00
Estudo autónomo	113,00
Total:	162,00

Eligibility for exams

Students should not exceed 4 absences in problem classes.

Calculation formula of final grade

The final grade formula depends on the student's choice of making 3 or 2 Homeworks.
For students who take 3TPCs the exam counts 70% and the continuous component 30%.
Students who choose not to take the third TPC, the exam counts 80% and the component continues 20%.
For approval, students must have at least 7.5 values in the exam and positive in the continuous evaluation.

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Examinations or Special Assignments

The continuous component is made with three homework that must be delivered in 48h. Each homework counts 10%.

Classification improvement

Only the exam grade can be improved.

Observations

Students who obtain a mark greter or equal to 17  must defend the grade in additional test.
The jury of the curricular unit includes:
João Manuel Viana Parente Lopes
Eduardo Filipe Vieira Castro
José Miguel Nunes da Silva