Go to:
Logótipo
You are in:: Start > FIS3018

Statistical Physics

Code: FIS3018     Acronym: FIS3018

Keywords
Classification Keyword
OFICIAL Physics

Instance: 2024/2025 - 1S Ícone do Moodle

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

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
L:B 4 Official Study Plan 3 - 6 48 162
L:CC 4 study plan from 2021/22 2 - 6 48 162
3
L:EF 96 study plan from 2021/22 3 - 6 48 162
L:F 63 Official Study Plan 3 - 6 48 162
L:G 0 study plan from 2017/18 2 - 6 48 162
3
L:M 0 Official Study Plan 2 - 6 48 162
3
L:MA 0 Official Study Plan 3 - 6 48 162
L:Q 0 study plan from 2016/17 3 - 6 48 162

Teaching Staff - Responsibilities

Teacher Responsibility
João Manuel Viana Parente Lopes

Teaching - Hours

Theoretical classes: 1,85
Theoretical and practical : 1,85
Type Teacher Classes Hour
Theoretical classes Totals 1 1,846
João Manuel Viana Parente Lopes 1,714
Theoretical and practical Totals 3 5,538
João Manuel Viana Parente Lopes 1,714
José Miguel do Carmo Nunes da Silva 1,714
João Pedro dos Santos Pires 1,714

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 85,00
Trabalho escrito 15,00
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 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 15% of
the final grade and the exam 85%.
In the evaluation without continuous component, the exam is worth 100%.


 


Examinations or Special Assignments

The continuous component is made with three homework that must be delivered in 5 days. Each homework counts 5%.

Internship work/project

Special assessment (TE, DA, ...)

Classification improvement

Only the exam grade can be improved.

Observations

Students who obtain a mark greater or equal to 17  must defend the grade in an additional test.
The jury of the curricular unit includes:
João Manuel Viana Parente Lopes
José Miguel Nunes da Silva
João Pedro dos Santos Pires
Recommend this page Top
Copyright 1996-2024 © Faculdade de Ciências da Universidade do Porto  I Terms and Conditions  I Acessibility  I Index A-Z  I Guest Book
Page created on: 2024-11-09 at 13:11:24 | Acceptable Use Policy | Data Protection Policy | Complaint Portal