NMAA13031U Dynamical Systems (DynSys)
Volume 2013/2014
Education
MSc programme in Mathematics
MSc programme in Statistics
MSc programme in Mathematics-Economics
MSc programme in Statistics
MSc programme in Mathematics-Economics
Content
A dynamical system is a
system which evolves as times goes by.
If the evolution law is fixed and deterministic, we are dealing with iterations of a transformation from a space into itself (discrete time) or an ordinary differential equation whose solution is a flow (continuous time). Many interesting examples arise in physics (mechanics - in particular the solar system - and statistical mechanics) but also number theory, computer science, chemistry, biology... The long time evolution is often unpredictable in practice ("chaos", "butterfly effect"), but a qualitative description is possible for many interesting classes of systems, using e.g. methods from probability theory and functional analysis. Topics which will be presented include:
-Topological dynamics (coding, topological entropy...).
-Ergodic theory (Poincaré theorem, Birkhoff theorem, Kolmogorov entropy, mixing, Shannon-McMillan-Breiman theorem, central limit theorem and correlations functions...)
-Differentiable dynamics (one-dimensional real dynamics, including use of the Perron-Frobenius transfer operator; hyperbolic dynamics in dimension two: stable and unstable manifolds, Hartman-Grobman theorem ...).
-Without proofs: Lyapunov exponents (Oseledec theorem, Ruelle inequality).
If the evolution law is fixed and deterministic, we are dealing with iterations of a transformation from a space into itself (discrete time) or an ordinary differential equation whose solution is a flow (continuous time). Many interesting examples arise in physics (mechanics - in particular the solar system - and statistical mechanics) but also number theory, computer science, chemistry, biology... The long time evolution is often unpredictable in practice ("chaos", "butterfly effect"), but a qualitative description is possible for many interesting classes of systems, using e.g. methods from probability theory and functional analysis. Topics which will be presented include:
-Topological dynamics (coding, topological entropy...).
-Ergodic theory (Poincaré theorem, Birkhoff theorem, Kolmogorov entropy, mixing, Shannon-McMillan-Breiman theorem, central limit theorem and correlations functions...)
-Differentiable dynamics (one-dimensional real dynamics, including use of the Perron-Frobenius transfer operator; hyperbolic dynamics in dimension two: stable and unstable manifolds, Hartman-Grobman theorem ...).
-Without proofs: Lyapunov exponents (Oseledec theorem, Ruelle inequality).
Learning Outcome
*Knowledge:
Know the fundamental concepts of the course in topological, differentiable, and ergodic dynamics,
*Skills:
Be able to analyse simple examples of topological or differentiable dynamical systems, such as determining transitiveness and mixing; invariance and ergodicity/mixing of a measure; computing the topological and Kolmogorov entropies or analysing the transfer operator in simple cases.
*Competences
Be able to exploit the main theorems of the course to solve dynamically formulated problems from physics, chemistry, or number theory.
Know the fundamental concepts of the course in topological, differentiable, and ergodic dynamics,
*Skills:
Be able to analyse simple examples of topological or differentiable dynamical systems, such as determining transitiveness and mixing; invariance and ergodicity/mixing of a measure; computing the topological and Kolmogorov entropies or analysing the transfer operator in simple cases.
*Competences
Be able to exploit the main theorems of the course to solve dynamically formulated problems from physics, chemistry, or number theory.
Academic qualifications
Top, An2. Also MI, KomAn
can be useful. Prior knowledge about manifold theory is not
needed.
Teaching and learning methods
2 x 2 hours lecture and 1x 3
hours exercises (teaching assistant) per week for 7
weeks.
Workload
- Category
- Hours
- Exam
- 24
- Guidance
- 26
- Lectures
- 28
- Preparation
- 107
- Theory exercises
- 21
- Total
- 206
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Continuous assessment, assignmentWritten examination, 3 hours under invigilationContinuous assessment based on two assignments, each counting for 20% of the grade and a 3-hour written exam, counting for the final 60% of the grade.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
One internal examiner.
- Re-exam
- Same as ordinary exam but notice that the assignments may be redone or the original assignments may count.
Criteria for exam assesment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome.
Course information
- Language
- English
- Course code
- NMAA13031U
- Credit
- 7,5 ECTS
- Level
- Full Degree MasterBachelor
- Duration
- 1 block
- Placement
- Block 4
- Schedule
- A
- Course capacity
- No limit
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Course responsibles
- Viviane Baladi (baladi@math.ku.dk)
Phone +45 35 32 07 91, office
04.1.13
Saved on the
30-04-2013