Course Information
SemesterCourse Unit CodeCourse Unit TitleL+PCreditNumber of ECTS Credits

Course Details
Language of Instruction English
Level of Course Unit First Cycle
Department / Program MATHEMATICS
Mode of Delivery Face to Face
Type of Course Unit Elective
Objectives of the Course Quantum computation and information is a new and rapidly developing field. This course is a concise introduction to quantum computation, developing the basic elements of this new branch of computational theory . The course intended primarily for mathematics, physics, engineering and computer science students. No prior knowledge either of quantum mechanics or of classical computation is required.
Course Content After providing the necessary background material in classical computation and quantum mechanics, the basic principles will be developed and the main results of quantum computation and information will be discussed.
Introduction to Classical Computation: The Turing machine. The circuit model of computation. Computational complexity. Energy and information. Reversible computation.
Introduction to Quantum Mechanics: The Stern-Gerlach experiment. Young’s double-split experiment. Linear vector spaces. The postulates of quantum mechanics. The EPR paradox and Bell’s inequalities.
Quantum Computation.
Quantum Communication: The no-cloning theorem. Faster-than-light transmission of information. Quantum teleportation.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Prof.Dr. OKTAY PASHAEV
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources G. Benenti, G. Casati and G. Strini. Principles of Quantum Computation and Information, Vol. 1: Basic Concepts.
David Mermin, Quantum Computer Science, An Introduction, Cambridge University Press, 2007
Nielsen Chuang and Isaac Chuang, Introduction to Quantun Computation and Information.

Course Category

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Midterm exams 1 % 30
Quizzes 0 % 0
Homeworks 1 % 10
Other activities 0 % 0
Laboratory works 0 % 0
Projects 1 % 10
Final examination 1 % 50
% 100

ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Weekly Course Time 1 72 72
Outside Activities About Course (Attendance, Presentation, Midterm exam,Final exam, Quiz etc.) 1 42 42
Exams and Exam Preparations 1 72 72
Total Work Load   Number of ECTS Credits 6 186

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 The ability to understand and apply mathematical techniques for solving problems. (PO 1)
2 To distinguish mathematical language to solve concrete problems. (PO 2)
3 To be able to write and speak about subjects. (PO 3)
4 The ability to demonstrate knowledge of basic mathematical theorems. (PO 5)
5 To be able to prove basic mathematical theorems. (PO 11)

Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to Classical Computation.
2 Classical Computation.
3 Introduction to Quantum Mechanics.
4 Postulates of Quantum Mechanics.
5 Quantum Computation.
6 Qubit Gates.
7 Midterm
8 Universal Quantum Gates.
9 The Quantum Fourier Transform.
10 Shor s Algorithm
11 Quantum Computers. First Implementations.
12 Quantum Communication.
13 Entanglement in Spin Models.
14 The Concurence and Entanglement.
15 Final 1st week
16 Final 2nd week

Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14
C1 3 3 3 3 3
C2 0 3 3 3 3
C3 3 3 3 3 3
C4 3 3 3 3 3
C5 3 3 3 3 3

Contribution: 0: Null 1:Slight 2:Moderate 3:Significant 4:Very Significant