- Lecturer: Jon Chapman
General Prerequisites:
Part A Differential Equations 2.
Course Term: Hilary
Course Lecture Information: 16 lectures
Course Weight: 1
Course Level: H
Assessment Type: Written Examination
Course Overview:
This course aims to provide an introduction to the tools and concepts of dynamical systems theory which have become a central tool of both pure and applied mathematics with applications in celestial mechanics, mathematical biology, fluid dynamics, granular media, and social sciences.
The course will focus on the geometry of both ordinary differential equations and maps. It will draw examples from appropriate model systems and various application areas. The problem sheets will require basic skills in numerical computation (numerical integration and visualisation of solutions of differential equations).
The first half of this course is part of the core syllabus for the MSc in Mathematical Modelling and Scientific Computing A2 Mathematical Methods. Synopsis items marked with * are NOT part of the MSc syllabus
The course will focus on the geometry of both ordinary differential equations and maps. It will draw examples from appropriate model systems and various application areas. The problem sheets will require basic skills in numerical computation (numerical integration and visualisation of solutions of differential equations).
The first half of this course is part of the core syllabus for the MSc in Mathematical Modelling and Scientific Computing A2 Mathematical Methods. Synopsis items marked with * are NOT part of the MSc syllabus
Learning Outcomes:
Students will have developed a sound knowledge and appreciation of some of the tools, concepts, and computations used in the study of dynamical systems. They will also get some exposure to some modern research topics in the field.
Course Synopsis:
1. Geometry of linear systems
Basic concepts of stability and linear manifold of solutions. Orbits in phase-space, linear flows, eigenvalues of fixed points.
2. Geometry on nonlinear systems
Notion of flows, invariant sets, asymptotic sets, attractor. Conservative and Non-Conservative systems.
3. Local analysis
Stable manifold theorem, notion of hyperbolicity, center manifold.
4. Bifurcation.
Bifurcation theory: codimension one normal forms (saddle-node, pitchfork, trans-critical, *Hopf). *Poincare-Lindstedt method.
5. *Maps
Poincaré sections and first-return maps. Stability and periodic orbits; bifurcations of one-dimensional maps, period-doubling.
6. *Chaos
Maps: Logistic map, Bernoulli shift map, symbolic dynamics, Smale's Horseshoe Map. Melnikov's method.
Basic concepts of stability and linear manifold of solutions. Orbits in phase-space, linear flows, eigenvalues of fixed points.
2. Geometry on nonlinear systems
Notion of flows, invariant sets, asymptotic sets, attractor. Conservative and Non-Conservative systems.
3. Local analysis
Stable manifold theorem, notion of hyperbolicity, center manifold.
4. Bifurcation.
Bifurcation theory: codimension one normal forms (saddle-node, pitchfork, trans-critical, *Hopf). *Poincare-Lindstedt method.
5. *Maps
Poincaré sections and first-return maps. Stability and periodic orbits; bifurcations of one-dimensional maps, period-doubling.
6. *Chaos
Maps: Logistic map, Bernoulli shift map, symbolic dynamics, Smale's Horseshoe Map. Melnikov's method.