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Quantum Computers, 6 credits
Kvantdatorer, 6 hp
TFYA19
Main field of study
Applied Physics PhysicsCourse level
Second cycleCourse type
Programme courseExaminer
Iryna YakymenkoDirector of studies or equivalent
Magnus JohanssonEducation components
Preliminary scheduled hours: 40 hRecommended self-study hours: 120 h
ECV = Elective / Compulsory / Voluntary
Main field of study
Applied Physics, PhysicsCourse level
Second cycleAdvancement level
A1XCourse offered for
- Applied Physics and Electrical Engineering, M Sc in Engineering
- Physics and Nanoscience, Master's programme
- Materials Science and Nanotechnology, Master's programme
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
Specific information
The course is not available 2017.
Prerequisites
Quantum mechanics, Thermodynamics and statistical mechanics, Quantum dynamicsIntended learning outcomes
The course represents a comprehensive survey on the concept of quantum computing with an exposition of qubits, quantum logic gates, quantum algorithms and implementation. Starting with the main definitions of the theory of computation, the course mostly deals with the application of the laws of quantum mechanics to quantum computing and quantum algorithms. Some related topics concerned mainly to the problem of quantum communication are also be considered. To achieve this aim students should be able to
- know the definition of qubit, quantum logic gates, quantum circuits and quantum algorithms
- understand how quantum parallelism is used in the simplest quantum algorithms such as Deutsch, period finding and quantum Fourier transform
- simulate the Feynman processor numerically
- know the basic requirements for implementation of quantum computers and classify the schemes for implementation of quantum computers
- review the selected original scientific papers about quantum computers and quantum information.
Course content
Computer organization and theory of computation: binary system, Boolean algebra, logic gates, quantum logic gates, algorithms, Turing machines and effective computability.
Quantum mechanics and computers: from bits to qubits,
superposition, measurement, classical and quantum coin-tosses, uncertainty principle.
Quantum algorithms: quantum parallelism, discrete Fourier transfom, phase estimation, Shor's factoring and Grover's searching algorithms.
Physical realization of quantum computation: ion trap,
cavity QED, nuclear magnetic resonance (NMR) and solid-state-based quantum computers.
Quantum cryptography, quantum teleportation and
quantum error correction.
Teaching and working methods
The course contains lectures, solution of home problems, numerical projects, study visit in cryptolab.
Examination
| MUN1 | Oral examination, solutions of home problems | 6 credits | U, 3, 4, 5 |
Grades
,Department
Institutionen för fysik, kemi och biologiDirector of Studies or equivalent
Magnus JohanssonExaminer
Iryna YakymenkoCourse website and other links
http://www.ifm.liu.se/undergrad/fysikgtu/coursepage.html?selection=all&sort=kkEducation components
Preliminary scheduled hours: 40 hRecommended self-study hours: 120 h
Course literature
I.I. Yakymenko. Lecture Notes on Quantum Computers.M.A. Nielsen, I.L. Chuang. Quantum computation and quantum information,Cambridge University Press, 2011, 10th ed. (selected chapters), och valda vetenskapliga artiklar.
| Code | Name | Scope | Grading scale |
|---|---|---|---|
| MUN1 | Oral examination, solutions of home problems | 6 credits | U, 3, 4, 5 |
Course literature is preliminary.
I.I. Yakymenko. Lecture Notes on Quantum Computers.
<br>M.A. Nielsen, I.L. Chuang. Quantum computation and quantum information,Cambridge University Press, 2011, 10th ed. (selected chapters), och valda vetenskapliga artiklar.
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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X
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X
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MUN1
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| 1.2 Fundamental engineering knowledge (G1X level) |
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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X
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| 2.2 Experimentation, investigation, and knowledge discovery |
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| 2.3 System thinking |
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| 2.4 Attitudes, thought, and learning |
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X
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X
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| 2.5 Ethics, equity, and other responsibilities |
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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| 3.2 Communications |
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X
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MUN1
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| 3.3 Communication in foreign languages |
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X
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MUN1
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
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| 4.4 Designing |
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| 4.5 Implementing |
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| 4.6 Operating |
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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X
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| 5.4 Execution of research or development projects |
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X
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| 5.5 Presentation and evaluation of research or development projects |
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MUN1
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