ECTS - Introduction to Quantum Computing
Introduction to Quantum Computing (CMPE456) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Introduction to Quantum Computing | CMPE456 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Discussion, Drill and Practice, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | To equip students to have a clear understanding of how Quantum computers work and how to apply and develop algorithms to be executed on quantum computers. Students will be given the basics to understand quantum operations and briefly introduced to Quantum theory. Students will execute real Quantum programs on real and simulated Quantum computers, study topics about Quantum algorithms, architecture, programming languages, cryptography, hardware and present their studies in class. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | The features of the Quantum World, complex numbers, complex vector spaces, probabilistic and Quantum systems, basic Quantum Theory, Qubits, Quantum gates, Quantum algorithms, Quantum computing in theoretical computer science, introduction to Quantum cryptography, Introduction to Quantum information theory, Introduction to Quantum hardware. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Course Introduction, Introduction to Quantum World, Spin, Real-Life Quantum Experiment Quantum Computing for Everyone – Chapter 1 | Quantum Computing for Everyone – Chapter 1 |
| 2 | The Features of The Quantum World, Complex Numbers Course Book – Chapter 1 | Course Book – Chapter 1 |
| 3 | Complex Vector Spaces | Course Book – Chapter 2 |
| 4 | Probabilistic Systems, Quantum Systems | Course Book – Chapter 3 |
| 5 | Basic Quantum Theory | Course Book – Chapter 4 |
| 6 | Quantum Architecture: Qubits, Quantum Gates | Course Book – Chapter 5 |
| 7 | Midterm Exam | |
| 8 | Quantum Algorithms: Deutsch’s Algorithm, The Deutsch-Jozsa Algorithm | Course Book – Chapter 6 |
| 9 | Quantum Algorithms: Simon’s Periodicity Algorithm, Grover’s Search Algorithm | Course Book – Chapter 6 |
| 10 | Shor’s Factoring Algorithm, Programming in a Quantum World | Course Book – Chapter 6,7 |
| 11 | Deterministic, Nondeterministic, Probabilistic and Quantum Computations | Chapter 8 |
| 12 | Quantum Cryptography and Teleportation | Course Book – Chapter 9 |
| 13 | Quantum Information Theory and Error-Correcting Codes | Course Book – Chapter 10 |
| 14 | Quantum Hardware: Goals and Challenges | Course Book – Chapter 11 |
| 15 | Review | |
| 16 | Final Exam |
Sources
| Course Book | 1. Quantum Computing for Computer Scientists, Noson S. Yanofsky, and Mirco A. Mannucci, Publisher: Cambridge University Press, 2008. |
|---|---|
| Other Sources | 2. IBM Quantum Learning: https://learning.quantum.ibm.com/ |
| 3. Quantum Computation and Quantum Information, 10th Anniversary Edition, Michael A. Nielsen, and Isaac L. Chuang, Publisher: Cambridge University Press, December, 2010. | |
| 4. Quantum Computing for Everyone, Chris Bernhardt, Publisher: MIT Press, 2020. | |
| 5. Quantum Computing from the Ground Up, Riley Tipton Perry, 2012. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | 2 | 20 |
| Homework Assignments | - | - |
| Presentation | 1 | 20 |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 25 |
| Final Exam/Final Jury | 1 | 35 |
| Toplam | 5 | 100 |
| Percentage of Semester Work | 65 |
|---|---|
| Percentage of Final Work | 35 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | An ability to apply advanced knowledge of computing and/or informatics to solve software engineering problems. | |||||
| 2 | Develop solutions using different technologies, software architectures and life-cycle approaches. | |||||
| 3 | An ability to design, implement and evaluate a software system, component, process or program by using modern techniques and engineering tools required for software engineering practices. | |||||
| 4 | An ability to gather/acquire, analyze, interpret data and make decisions to understand software requirements. | |||||
| 5 | Skills of effective oral and written communication and critical thinking about a wide range of issues arising in the context of working constructively on software projects. | |||||
| 6 | An ability to access information in order to follow recent developments in science and technology and to perform scientific research or implement a project in the software engineering domain. | |||||
| 7 | An understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering. | |||||
| 8 | Skills in project and risk management, awareness about importance of entrepreneurship, innovation and long-term development, and recognition of international standards of excellence for software engineering practices standards and methodologies. | |||||
| 9 | An understanding about the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions. | |||||
| 10 | Promote the development, adoption and sustained use of standards of excellence for software engineering practices. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 2 | 32 |
| Presentation/Seminar Prepration | 1 | 10 | 10 |
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | 2 | 5 | 10 |
| Prepration of Midterm Exams/Midterm Jury | 1 | 10 | 10 |
| Prepration of Final Exams/Final Jury | 1 | 15 | 15 |
| Total Workload | 125 | ||