Login for PhD students/staff at UCPH      Login for others
Complex Physics - PhD course
Provider: Faculty of Science

Activity no.: 5851-20-11-31 
Enrollment deadline: 31/08/2020
Date and time31.08.2020, at: 00:00 - 08.11.2020, at: 16:00
Regular seats25
ECTS credits7.50
Contact personJulie Meier    E-mail address: juliemh@nbi.ku.dk
Enrolment Handling/Course OrganiserKim Sneppen    E-mail address: sneppen@nbi.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 1
Block noteBlock 1 - Schedule A
Scheme groupA (Tues 8-12 + Thurs 8-17)
Exam formOral examination
Exam detailsOral exam without preparation time
Exam aidsWithout aids
Grading scale7 point grading scale
Censorship formSeveral internal examiners
Exam re-examinationSame as ordinary exam
Course workload
Course workload categoryHours
Lectures24.00
Theory exercises28.00
E-learning2.50
Eksamen20.50
Preparation131.00

Sum206.00


Content
The topics that will be covered are: Phase transitions, Ising model, critical phenomena, Monte Carlo simulations, Percolation, Networks, interfaces, agent-based models, self organization, scale free phenomena, game theory, econophysics and models of social systems.

Formel requirements
Important information for students outside of Denmark:
To apply for participation in this course, it is required that you send an email to the course organizer with your information and motivation for joining the course. Do not use the online application. Thank you.

Learning outcome
Skills

The aim is to learn how to rephrase a complex phenomenon into a mathematical equation or computer algorithm. At the conclusion of the course students will be able to implement and analyze simple quantitative models on a computer. Students will learn how to appreciate that the joint dynamics of a many body system often is qualitatively different from the simple sum of its parts.



Knowledge

The student is expected to gain basic knowledge on contemporary research in complex systems. This includes the ability to use fundamental concepts from statistical mechanics, non-linear dynamics, time series analysis, agent based models and self-organizing systems. This includes the concepts of scaling and scale-invariant phenomena, e.g. fractals or scale-free networks.



Competences

How to describe and analyze non-linear systems and systems with many components in terms of equations and algorithms.

Write computer models of systems with many interacting parts, including Monte-Carlo simulations, interfaces, networks, and cellular automata.

Implement agent based models to describe self-organized dynamics of structures, for example within network theory and systems that behave similar across a wide range of scales.



The course will provide the students with tools from physics that have application in a range of fields within and beyond physics.

Literature
Lecture notes

Teaching and learning methods
Lectures and exercises

Lecturers
Jan Haerter
Mogens Høgh Jensen

Search
Click the search button to search Courses.


Course calendar
See which courses you can attend and when
JanFebMarApr
MayJunJulAug
SepOctNovDec



Publication of new courses
All planned PhD courses at the PhD School are visible in the course catalogue. Courses are published regularly.