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Complex physics - PhD course
Provider: Faculty of Science

Activity no.: 5851-21-11-31
Enrollment deadline: 30/07/2021
Date and time06.09.2021, at: 00:00 - 12.11.2021, at: 16:00
Regular seats20
ECTS credits7.50
Contact personJulie Meier Hansen    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 scalePassed / Not passed
Criteria for exam assessmentWritten assignment Oral examination, 30 minutes The exam consists of two parts; One assignment (counting 20% of the final grade) Oral exam without preparation time (counting 80% of the final grade)
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.

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.

Target group

This course is offered to both MSc and PhD students. Link to the MSc course >> here

PhD students: please see below for sign-up information.


Teaching and learning methods
Lectures and exercises

Remarks

Recommended Academic Qualifications:

Students would gain by having taken a course on Dynamical Systems and Chaos, as well as by having some knowledge of statistical mechanics and knowledge of some programming language. These requirements are however non-mandatory, and with some effort the course can be followed by other students, in particular students with background in mathematics, bio-informatics, economics or computer sciences.

Applying for the course:
If you are a PhD student, please apply as a credit student at this link.

The course code to enter is NFYK18005U. 

Please contact Julie Meier Hansen if you have any questions or problems with signing up.






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