Undergraduate Course: Introduction to Quantum Computing (INFR11256)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Year 4 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | The aim of this course is to give students a basic overview of the rapidly growing field of Quantum Computation (QC). The course will start with a brief introduction of the mathematical framework of QC. The two models of quantum circuit and measurement-based quantum computing will be introduced. We cover the most important quantum subroutines and their application to wellknown quantum algorithms and compare their performance with respect to classical computing. Additionally, we survey existing quantum programming platforms. We finish the course by surveying few more advanced topics, such as quantum error correction, algorithms for near-term architectures, quantum machine learning and secure delegated QC. |
| Course description |
- Basic concepts from Linear Algebra necessary for understanding the axioms of Quantum Mechanics.
- Axioms of Quantum Mechanics, describing quantum system, quantum operators, composition, entanglement and measurements.
- Quantum Computing via quantum circuit model: Description of qubit and universal set of gates.
- Quantum subroutines such as Phase Kick-back, Quantum Fourier Transform, Hadamard Test or Phase-Estimation.
- Quantum Algorithms such as Grover's Search, Deutsch-Jozsa, Bernstein-Vazirani or Shor.
- Quantum Computing via measurement-based model: Description of graph state and measurement calculus.
- Quantum Programming: online platforms and languages.
- Advanced Topics: quantum error correction, algorithm for near-term architectures, quantum machine learning, unconditionally secure quantum cloud computing.
|
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2024/25, Available to all students (SV1)
|
Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 30,
Seminar/Tutorial Hours 8,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
158 )
|
| Assessment (Further Info) |
Written Exam
75 %,
Coursework
25 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Written Exam ___75__%
Practical Exam ___0__% (for courses with programming exams)
Coursework __25___% |
| Feedback |
Oral feedback during tutorials and on coursework. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Use the mathematical framework of quantum computation to predict outcomes of quantum circuits.
- Explain and analyse quantum subroutines and algorithms described in quantum circuit and measurement-based quantum computing models.
- Discuss the difference of performance between classical and quantum computer for different computational tasks.
- Master notions of more advanced topics, such as error correction on algorithms for near-term architectures.
- Use available quantum programming platforms.
|
Reading List
| See https://opencourse.inf.ed.ac.uk/iqc/resource-list |
Additional Information
| Graduate Attributes and Skills |
Research and enquiry: problem-solving, critical/analytical thinking, knowledge integration
Personal effectiveness: planning and organizing
Personal responsibility and autonomy: independent learning, creativity
Communication: written communication skills, programming skills |
| Keywords | Quantum Computing |
Contacts
| Course organiser | Dr Petros Wallden
Tel: (0131 6)51 5631
Email: petros.wallden@ed.ac.uk |
Course secretary | |
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