Information Package / Course Catalogue
| Computer Engineering | |||||
| Bachelor | Length of the Programme: 4 | Number of Credits: 240 | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF: Level 6 |
Ders Genel Tanıtım Bilgileri
| School/Faculty/Institute | Faculty of Engineering | |||||
| Course Code | COMP 465 | |||||
| Course Title in English | Fundamentals of Quantum Computing | |||||
| Course Title in Turkish | Kuantum Hesaplama Temelleri | |||||
| Language of Instruction | EN | |||||
| Type of Course | Flipped Classroom | |||||
| Level of Course | Introductory | |||||
| Semester | Spring | |||||
| Contact Hours per Week |
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| Estimated Student Workload | 145 hours per semester | |||||
| Number of Credits | 6 ECTS | |||||
| Grading Mode | Standard Letter Grade | |||||
| Pre-requisites |
MATH 211 - Linear Algebra MATH 224 - Probability and Statistics for Engineering |
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| Expected Prior Knowledge | Exposure to some form of programming | |||||
| Co-requisites | None | |||||
| Registration Restrictions | Only Undergraduate Students | |||||
| Overall Educational Objective | To learn the fundamentals of quantum information and computing and explore various application areas. | |||||
| Course Description | This course explores the fundamentals of Quantum Information Science and Computation. The following important topics are covered: superposition, entanglement, quantum teleportation and the theory of measurement. The course will review and compare classical computation against quantum computation with several examples. We also intend to give assignments to use IBM’s real quantum computers available on the cloud to get students a hands-on experience on this new emerging field. Towards the end of the course, we shall provide details about few quantum algorithms and future trends such as Quantum Machine Learning (QML). In addition, some of the philosophical questions and the impact of Quantum computing to various fields of research will be discussed. | |||||
| Course Description in Turkish | Bu ders Kuantum Bilgi Bilimi ve Hesaplamanın temellerini inceleyecektir. Önemli olan şu konulara yer verilecektir: süperpozisyon, dolaşıklık, kuantum ışınlanma ve ölçüm teorisi. Ders, kuantum hesaplamaya karşı klasik hesaplamayı gözden geçirecek ve birkaç örnekle karşılaştıracaktır. Ayrıca, öğrencilere bu yeni ortaya çıkan alanda uygulamalı bir deneyim kazandırmak için IBM’in bulut üzerinde bulunan gerçek kuantum bilgisayarlarını kullanma ödevleri verilecektir. Dersin sonuna doğru, birkaç kuantum algoritması ve Kuantum Makine Öğrenimi (QML) gibi gelecekteki eğilimler hakkında ayrıntılar paylaşacağız. Ayrıca, felsefik soruların bazıları ve kuantum hesaplamanın çeşitli araştırma alanlarına etkisi tartışılacaktır. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) describe quantum mechanics and fundamental principles of quantum computing; 2) describe and construct quantum circuits using online tools; 3) apply quantum circuits/algorithms to solve some of the hard problems; 4) analyze and apply basic principles of quantum communications; 5) describe and implement most notable quantum algorithms; 6) acquire and apply the knowledge of quantum technology for future trends. |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| 1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | ||||||
| 2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | ||||||
| 3) An ability to communicate effectively with a range of audiences | ||||||
| 4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | ||||||
| 5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | ||||||
| 6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | ||||||
| 7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. |
Relation to Program Outcomes and Competences
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | H | Exam,Participation |
| 2) | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | N | |
| 3) | An ability to communicate effectively with a range of audiences | N | |
| 4) | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | N | |
| 5) | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | N | |
| 6) | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | N | |
| 7) | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. | N |
| Prepared by and Date | ŞEFİK ŞUAYB ARSLAN , December 2020 |
| Course Coordinator | ŞEFİK ŞUAYB ARSLAN |
| Semester | Spring |
| Name of Instructor | Assoc. Prof. Dr. ŞEFİK ŞUAYB ARSLAN |
Course Contents
| Week | Subject |
| 1) | Introduction to Quantum Computing: Spin, photon, polarization |
| 2) | Postulates of Quantum Mechanics & linear algebra overview |
| 3) | Simple quantum computation model, qubit, quantum states (Ket notation), superposition, normalisation |
| 4) | Measurement of Quantum states |
| 5) | Classical Gates/Circuits and Reversible circuits |
| 6) | Quantum logic gates: CNOT and Hadamard gates |
| 7) | Universality, Unitary transformations, Phase change, rotation and Pauli gates |
| 8) | Quantum Entanglement and Bell’s inequality. No Cloning Theorem and Implications |
| 9) | Quantum Circuits: The Bell Circuit |
| 10) | Quantum Communication: Superdense coding and Quantum Teleportation |
| 11) | Simple Quantum Error Correction |
| 12) | Quantum Algorithms I: Deutch’s Algorithm, Deutsch-Jozsa Algorithm |
| 13) | Quantum Algorithms II: Simon’s Algorithm, Grover’s search Algorithm, Shor’s Algorithm |
| 14) | The Impact of Quantum computing and advanced use cases such as QML |
| 15) | Final Examination/Project/Presentation Period |
| 16) | Final Examination/Project/Presentation Period |
| Required/Recommended Readings | Depending on the level of students, there are two references I frequently resort to (both are available online) i. Chris Bernhardt, Quantum Computing for Everyone, MIT Press, 1st Edition (2019) [More suitable for undergraduates] ii. Kaye, Phillip, Raymond Laflamme, and Michele Mosca. An Introduction to Quantum Computing. Oxford University Press, 2007. | ||||||||||||||||||
| Teaching Methods | Lectures/contact hours using “flipped classroom” as an active learning technique | ||||||||||||||||||
| Homework and Projects | There are 5 homeworks formulated much like small projects. | ||||||||||||||||||
| Laboratory Work | None | ||||||||||||||||||
| Computer Use | Required | ||||||||||||||||||
| Other Activities | - | ||||||||||||||||||
| Assessment Methods |
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| Course Administration |
arslans@mef.edu.tr Instructor’s office: 5th Floor Office hours: Tue 16:00-17:00. E-mail address: arslans@mef.edu.tr, Rules for attendance: Classroom practice contributes to 14% of the final grade. Missing a midterm: Provided that proper documents of excuse are presented, each missed midterm by the student will be given the grade of the final exam. No make-up will be given. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Academic dishonesty and plagiarism: YÖK Regulations |
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ECTS Student Workload Estimation
| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 1 | 3 | 1 | 70 | ||
| Homework Assignments | 5 | 6 | 2 | 40 | |||
| Midterm(s) | 1 | 12 | 1.5 | 13.5 | |||
| Final Examination | 1 | 20 | 2.5 | 22.5 | |||
| Total Workload | 146 | ||||||
| Total Workload/25 | 5.8 | ||||||
| ECTS | 6 | ||||||