Information Package

Program of Computer Engineering (English 30%)

BİL457

INTRODUCTION TO QUANTUM COMPUTING

Course Code
BİL457
Semester
-
Theory+Practice
3 + 0
ECTS
5
Course TypeElective Course
Course LevelBachelor's Degree
Year of Study-
Semester-
ECTS5
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. Learn Quantum computer , quantum computing, quantum mechanics.
  2. Learn basic quantum computation.
  3. Learn quantum correlation.
  4. Learn Quantum Algorithms.
  5. Learn Quantum information.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionIntroduction and overview: qubits and pieces. Bloch sphere. Quantum mechanical probabilities. Quantum behaviors. Quantum mechanics with applications to teleportation. Dense coding. Quantum computation: Classical computation. Shor's factorization algorithm, Grover's search algorithm. Quantum information: Classical information theory. Quantum cryptography. Error correction. Physical realizations: Ions in traps. Solid-state devices.
Course Contents
WEEK TOPICS
1st Week Quantum Mechanics, Deterministic Systems, Probabilistic Systems, Quantum Systems
2nd Week Vector Spaces and Complex Numbers, Dirac Notation
3rd Week Linear Operators, Norm, Orthonormality, Gram-Schmidt
4th Week Scalar and Vector Product, Tensor Product, Pauli Matrices
5th Week Qubits and Entanglement
6th Week Observables and Measurements
7th Week Density Matrices, Partial Trace, EPR Paradox
8th Week MIDTERM EXAM
9th Week Logic Gates and Quantum Circuits
10th Week Quantum Fourier Transform (QFT)
11th Week Deutsch Algorithm, Simon Algorithm
12th Week Grover?s Search Algorithm
13th Week Shor Algorithm and Number Theory
14th Week Quantum Error Correction, Quantum Noise Models
15th Week Turing Machines, Probabilistic and Quantum Turing Machines, FINAL EXAM
Recommended or Required Reading1- Kaye P., Laflamme R., Mosca M., An Introduction to Quantum Computing, Oxford Press,2007
2- Yanofsky N. S., Mannucci M. A., Quantum Computing for Computer Scientists, Cambridge Press,2008
Planned Learning Activities and Teaching Methods
  • Problem Solving
  • Questions/Answers
  • Lecture
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 35
Quiz 2 15
Total(%) 50
Contribution of In-term Studies to Overall Grade(%) 50
Contribution of Final Examination to Overall Grade(%) 50
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 1.5 1.5
Preparation for Quiz
Individual or group work
Preparation for Final exam 1 20 20
Course hours 14 3 42
Preparation for Midterm exam 1 15 15
Laboratory (including preparation)
Final exam 1 1.5 1.5
Homework
Project 1 70 70
Quiz 4 0.5 2
Total Work Load152
Total Work Load / 30 (h)5.06
ECTS Credit of the Course5
Language of InstructionTurkish
Work Placement(s)No
LO1 LO2 LO3 LO4 LO5
K1 X X X X X
K2 X X X
K3
K4 X X X
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