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2020　Vector and Functional analysis

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Academic unit or major
Undergraduate major in Mathematical and Computing Science
Instructor(s)
Nishibata Shinya  Takahashi Jin 
Class Format
Lecture / Exercise    (ZOOM)
Media-enhanced courses
Day/Period(Room No.)
Mon3-4(W834)  Thr3-4(W834)  Thr7-8(W834)  
Group
-
Course number
MCS.T301
Credits
3
Academic year
2020
Offered quarter
2Q
Syllabus updated
2020/9/18
Lecture notes updated
-
Language used
Japanese
Access Index

Course description and aims

We will present the vector analysis and the functional analysis as the fundamental tools for the mathematical analysis.
The first half of this course is devoted to the calculus of scalar fields, vector fields.
In the last half of this course the fundamentals of the functional analysis such as Banach spaces, linear operators, Hilbert spaces, orthogonal decompositions and the Riesz representation theorem are given.

Student learning outcomes

The object of this course is to explain the vector analysis and the functional analysis as the fundamental tools for the mathematical analysis.
By completing this course, students will be able to:
1) understand the integrals of vector fields and master various integral formula.
2) understand fundamental properties of the Banach spaces and linear operators, the orthogonal decomposition and the Riesz representation theorems are given.

Keywords

vector fields, integral formula, Banach space, linear operators, Hilbert space

Competencies that will be developed

✔ Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

For the understanding of this course, it is necessary to be skilled at the contents by the calculation by hand. Therefore the exercise class is given every two weeks.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Scalar fields, vector fields Understand the contents of the lecture.
Class 2 Parametrization for curves and surfaces Understand the contents of the lecture.
Class 3 Exercise for scalar fields and vector fields, parametrization for curves and surfaces Cultivate a better understanding of lectures.
Class 4 Gradient, divergence and rotation Understand the contents of the lecture.
Class 5 Contour integral and surface integral Understand the contents of the lecture.
Class 6 Exercise for gradient, divergence, rotation, contour integral and surface integral Cultivate a better understanding of lectures.
Class 7 Green's formula, Gauss' divergence theorem Understand the contents of the lecture.
Class 8 Stokes' theorem Understand the contents of the lecture.
Class 9 Exercise for integral formula Cultivate a better understanding of lectures.
Class 10 Contraction mapping principle Understand the contents of the lecture.
Class 11 Banach space Understand the contents of the lecture.
Class 12 Exercise for contraction mapping principle and Banach space Cultivate a better understanding of lectures.
Class 13 Bounded linear operator Understand the contents of the lecture.
Class 14 Hilbert spaces Understand the contents of the lecture.
Class 15 Exercise for bounded linear operators and Hilbert spaces Cultivate a better understanding of lectures.
Class 16 Orthonormal system Understand the contents of the lecture.
Class 17 Orthogonal decomposition theorem Understand the contents of the lecture.
Class 18 Exercise for orthonormal system and orthogonal decomposition theorem Cultivate a better understanding of lectures.
Class 19 Riesz representation theorem Understand the contents of the lecture.
Class 20 Spectrum theorem Understand the contents of the lecture.
Class 21 Exercise for Riesz representation theorem and Spectrum theorem Cultivate a better understanding of lectures.

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend a certain length of time outside of class on preparation and review (including for assignments), as specified by the Tokyo Institute of Technology Rules on Undergraduate Learning (東京工業大学学修規程) and the Tokyo Institute of Technology Rules on Graduate Learning (東京工業大学大学院学修規程), for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

To be announced

Reference books, course materials, etc.

To be announced

Assessment criteria and methods

By scores of the examination and the reports.

Related courses

  • LAS.M101 ： Calculus I / Recitation
  • LAS.M105 ： Calculus II
  • LAS.M102 ： Linear Algebra I / Recitation
  • LAS.M106 ： Linear Algebra II

Prerequisites (i.e., required knowledge, skills, courses, etc.)

The students are encouraged to understand the fundamentals in the calculus and the linear algebras.

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