Learning objectives
Students must demonstrate knowledge and understanding of the basic results of the theory of locally convex spaces and distributions.
In particular, students must
1. exhibit solid knowledge and thorough conceptual understanding of the subject;
2. be able to communicate in a clear and precise way the contents of the course;
3. be able to access autonomously the scientific literature on the subject.
Prerequisites
Previous courses in algebra, topology and mathematical analysis.
Course unit content
Introduction to the theory of locally convex spaces and distributions.
Full programme
1) Locally convex spaces and weak topologies. 2) Test function spaces and distributions. 3) Fourier transform. 4) Application to PDEs.
Bibliography
W. Rudin, "Functional Analysis", 2nd Edition, McGraw-Hill Inc., New York 1991.
Teaching methods
Lectures (5 hours per week).
Assessment methods and criteria
The final exam consists of an oral examination.
Other information
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2030 agenda goals for sustainable development
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