Classical and quantum information theory

Course: Applied mathematics

Structural unit: Faculty of Computer Science and Cybernetics

Title
Classical and quantum information theory
Code
ДВС.3.01
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
9
Learning outcomes
PLO12.3. Understand the main areas of mathematical logic, theory of algorithms and computational theory, programming theory, probability theory and mathematical statistics. PLO13.3. Be able to use professional knowledge, skills and abilities in the field of fundamental sections of mathematics and computer science for research of real processes of different nature.
Form of study
Full-time form
Prerequisites and co-requisites
To successfully learn the discipline the student should satisfy the following requirements. They know (a) classical courses “Calculus”, “Linear algebra”, “Functional Analysis”, “Probability theory” They can (a) analyze the nature and goals of construction of mathematical structures and models; (b) apply classical commutative methods and construct their non-commutative analogs for solving of actual problems of operator theory and information theory. They should be able to (a) apply classical methods of Linear Algebra, Calculus and Functional Analysis, Probability Theory (b) seek information in open sources and properly analyze it.
Course content
The discipline of the second block is aimed at learning basic results of the Operator Algebras theory and mastering technical tools for applications in related areas of applied mathematics. The subject matters includes classical theorems of spectral theory, commutative Banach and C*-algebras, realisation of abstract C*-algebras by Hilbert space operators, structure theorems for the families of orthogonal projections. Applications of the results mentioned above in quantum information theory. The presented course is a natural continuation of the disciplines “Linear Algebra” and “Functional Analysis”.
Recommended or required reading and other learning resources/tools
1. Wegge-Olsen N.E. K-Theory and C*-algebras: a friendly approach. New-York: Oxford Science Publications. The Clarendon Press, Oxford University Press, 1993. – 370 p. 2. Hille E., Phillips R.S. Functional analysis and semigroups. Providence: AMS, 1974.—808 p. 3. Conway J.W.. A Course in Functional Analysis. Second edition. Graduate Texts in Mathematics, 96. New York: Springer-Verlag,1990. – 399 p. 4. S.M. Barnett, Quantum information theory. Oxford University Press, 2009, 300 p.
Planned learning activities and teaching methods
Lectures, consultations, test works, independent work.
Assessment methods and criteria
Intermediate assessment: The maximal number of available points is 60. Test work no. 1: 25/15 points. Test work no. 2: 25/15 points. Test work no. 1: 25/15 points. Test work no. 2: 25/15 points. Final assessment (in the form of credit): Results in semester’s marks.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Ihor V. Samoilenko
Operations Research
Faculty of Computer Science and Cybernetics

Departments

The following departments are involved in teaching the above discipline

Operations Research
Faculty of Computer Science and Cybernetics