Graduate
Institute of Graduate Studies
Mathematics (PHD)
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Topological Vector Spaces

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
DMB0016 Topological Vector Spaces 3/0/0 DE Turkish 8
Course Goals
Understanding the general theory of topological vector spaces.
Prerequisite(s) MBY0023 General Topology and MBY0022 Methods of Functional Analysis
Corequisite(s) None
Special Requisite(s) Proficiency in English, enough to be able to follow graduate texts in Mathematics.
Instructor(s) Professor Mert ÇAĞLAR
Course Assistant(s) None
Schedule Will be announced in the forthcoming term.
Office Hour(s) Assoc. Prof. Dr. Mert ÇAĞLAR, AK/3-A-03/05
Teaching Methods and Techniques -Lecture and homeworks.
Principle Sources -R. Meise & D. Vogt, Introduction to Functional Analysis, Translated by M.S. Ramanujan, Clarendon Press, Oxford, 1997.
Other Sources -H. Jarchow, Locally Convex Spaces, B.G. Teubner, Stuttgart, 1981.

-G. Köthe, Topological Vector Spaces I, II, Springer-Verlag, Berlin-Heidelberg-New York,1969, 1979.

-H.H. Schaefer, Topological Vector Spaces, Springer-Verlag, Berlin-Heidelberg-New York, 1971.
Course Schedules
Week Contents Learning Methods
1. Week Introduction to topological vector spaces Lecture and homework
2. Week Locally-convex topological vector spaces Lecture and homework
3. Week Inductive and projective limits I Lecture and homework
4. Week Inductive and projective limits II Lecture and homework
5. Week Fréchet spaces I Lecture and homework
6. Week Fréchet spaces II Lecture and homework
7. Week Montel and Schwartz spaces Lecture and homework
8. Week Midterm Exam Midterm Exam
9. Week Nuclear spaces Lecture and homework
10. Week Bases in Fréchet spaces I Lecture and homework
11. Week Bases in Fréchet spaces II Lecture and homework
12. Week Köthe sequence spaces I Lecture and homework
13. Week Köthe sequence spaces II Lecture and homework
14. Week Linear topological invariants Lecture and homework
15. Week Final Exam Week Final Exam
16. Week Final Exam Week Final Exam
17. Week Final Exam Week Final Exam
Assessments
Evaluation tools Quantity Weight(%)
Midterm(s) 1 30
Homework / Term Projects / Presentations 7 30
Final Exam 1 40


Program Outcomes
PO-1Have ability to develop new mathematical ideas and methods by using high-level mental processes such as creative and critical thinking, problem solving and decision-making.
PO-2Follow the current developments in the field of mathematics, and make the critical analysis, synthesis and evaluation of new and complex ideas.
PO-3Understand the interdisciplinary interaction related to Mathematics and play a role in an effective manner in environments that require with the resolution of problems encountered in this process.
PO-4Defend original views on the discussion of the issues in the field of mathematics with experts and communicate to show competence in oral and written.
PO-5Do research with high-level national and international scientific working groups, and acquire the responsibility to contribute to the literature by publishing original works in respected scientific journals.
PO-6Use computer software to solve problems effectively by following the developments in information and communication technologies.
PO-7Contribute to the solution of social, scientific, cultural and ethical problems encountered issues related to the field and support the development of these values.
PO-8To solve problems related to the field, establish functional interacts by using strategic decision making processes.
PO-9Establish and discuss in written, oral and visual communication at an advanced level by using at least one foreign language.
Learning Outcomes
LO-1Understanding the basic properties of topological vector spaces.
LO-2Understanding the structure of locally-convex topological vector spaces.
LO-3Understanding and analyzing inductive and projective limits.
LO-4Understanding and analyzing the structure of Frechet, Montel, Schwartz, and nuclear spaces.
LO-5Understanding and analyzing bases in Frechet spaces, Köthe sequence spaces, and linear topological invariants.
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9
LO 1
LO 2
LO 3
LO 4
LO 5