Syllabus for Applied Dynamical Systems

Tillämpade dynamiska system

Syllabus

  • 5 credits
  • Course code: 1MA151
  • Education cycle: First cycle
  • Main field(s) of study and in-depth level: Mathematics G1F

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle
    G1N: has only upper-secondary level entry requirements
    G1F: has less than 60 credits in first-cycle course/s as entry requirements
    G1E: contains specially designed degree project for Higher Education Diploma
    G2F: has at least 60 credits in first-cycle course/s as entry requirements
    G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    GXX: in-depth level of the course cannot be classified.

    Second cycle
    A1N: has only first-cycle course/s as entry requirements
    A1F: has second-cycle course/s as entry requirements
    A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    AXX: in-depth level of the course cannot be classified.

  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2010-03-18
  • Established by:
  • Revised: 2018-08-30
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 30, 2019
  • Entry requirements: Ordinary Differential Equations I or corresponding course, Scientific Computing I
  • Responsible department: Department of Mathematics

Learning outcomes

This course aims to provide insight and practice in how dynamical system (i.e. differential equation and difference equation) models can be used to better understand biology, physics, biochemistry, economics and sociology. The focus will be on formulating models, model analysis, using numerical solution tools to better understand models and drawing conclusions based on model outcomes.
Since the course contents is rather wide a focus will be made on increasing overall confidence in mathematical modelling, rather than deep study of each particular area. On completion of the course, the student should be able to:

  • formulate important models treated during the course;
  • outline the mathematical methods and techniques that are used to analyse these models and understand in what situations these methods can be applied;
  • understand how to draw a conclusion from a model;
  • use a computer package to investigate models numerically;
  • solve standard problems within the areas covered by the course.

Content

The course will consist of first an overview/revision of the theory of ordinary differential and difference equation models. This will be followed by a series of cases studies. In each case study there will be an emphasis both on how to build a model of various systems (i.e. applications), mathematical analysis (i.e. techniques), and on how numerical solutions increase understanding.
Case studies
At least three case studies will be chosen from the following possibilities. Solving the case studies will involve a combination of mathematical analysis and numerical solution in MATLAB.
1, Molecular and cellular biology. Non-dimensionalisation; Michaelis-Menten kinetics; matched asymptotic expansions; models of neural firing; oscillations in biochemical systems (Britton 6.1-6.4; Strogatz 8.3).
2, Coupled oscillators. Flows on the circle; driven and coupled pendulums; global bifurcations; firefly flashing; Kuramoto model (Strogatz 4.5-4.6 and 8.4-8.7 and further material)
3, Biological motion. Introduction to partial differential equations; diffusion equation; Fisher's equation; travelling wave solutions; reaction-diffusion equations and pattern formation; Turing bifurcations (Britton 5; Britton 7).
4, Chaos. Population dynamics and one-dimensional maps. Cobweb diagrams; periodic windows; Liapunov exponent

Instruction

Lectures, problem solving and computer laboratories.

Assessment

Written examination combined with assignments given during the course. 
 
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Reading list

Reading list

Applies from: week 30, 2019

  • Strogatz, Steven H. Nonlinear dynamics and chaos : with applications to physics, biology, chemistry and engineering

    Reading, Mass.: Addison-Wesley, 1994

    Find in the library

    Mandatory