F7110 Introduction to Monte Carlo simulation as a numerical tool

Faculty of Science
Autumn 2019
Extent and Intensity
1/1/0. 3 credit(s). Type of Completion: k (colloquium).
Teacher(s)
Dominique Alain Geffroy, Ph.D. (lecturer)
Guaranteed by
Dominique Alain Geffroy, Ph.D.
Department of Condensed Matter Physics – Physics Section – Faculty of Science
Contact Person: Dominique Alain Geffroy, Ph.D.
Supplier department: Department of Condensed Matter Physics – Physics Section – Faculty of Science
Timetable
Mon 12:00–12:50 Kontaktujte učitele
  • Timetable of Seminar Groups:
F7110/01: Mon 13:00–13:50 Kontaktujte učitele
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
During this course, the students will be exposed to Monte Carlo method as a flexible and powerful numerical tool for solving a variety of problems, going from statistical mechanics to financial derivatives valuation, including some simple quantum physics phenomena. The sessions will include a lecture introducing the concepts, followed by practice sessions started in class, to be completed from home as a homework. A large emphasis will be put on the use by the students of good coding practices and efficient workflow, which will be introduced in class and during the practice sessions. Python is the recommended language for following the course, but other languages are possible, depending on the students' experience, as long as they allow for object oriented design.
Syllabus
  • Monte Carlo algorithms: basics.
  • From dynamics to statistical mechanics.
  • Phase transitions
  • Integration by sampling
  • Quantum mechanics I: introduction to path integrals
  • Quantum mechanics II: Bose Einstein condensation
  • Statistical Physics: Ising model
  • Monte Carlo and financial models
Teaching methods
NB: The practice sessions will be the opportunity for the students to practice the following concepts, introduced in class: Introduction to Python, source control, coding workflow Object Oriented programming, efficient code design.
Assessment methods
"continuous assessment", where the quality of the work of the students on the exercises given in class along the semester determines their grade.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course is taught annually.
The course is also listed under the following terms Autumn 2016, autumn 2017, spring 2018, Autumn 2018, Spring 2019, Autumn 2020, autumn 2021, Autumn 2022.
  • Enrolment Statistics (Autumn 2019, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2019/F7110