Subject » BMEVIHIMA24
Quantum Computers and their Applications
Kvantumszámítógépek és alkalmazásaik
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
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| Subject name (Hungarian, English) |
Kvantumszámítógépek és alkalmazásaik
Quantum Computers and their Applications
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Subject code | BMEVIHIMA24 | ||||||||||||
| Subject type | — | ||||||||||||
| Training Level | — | ||||||||||||
| Course types and hours (weekly/semester) |
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| Assessment type | vizsga | ||||||||||||
| Credits | 5 | ||||||||||||
| Subject coordinator |
DR. Imre Sándor Zsolt
position: egyetemi tanár
contact:
imre.sandor@vik.bme.hu
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| Responsible department |
Hálózati Rendszerek és Szolgáltatások Tanszék
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| Faculty | Villamosmérnöki és Informatikai Kar | ||||||||||||
| Subject website | — | ||||||||||||
| Primary curriculum type | — | ||||||||||||
| Direct prerequisites – Strong prerequisite | none | ||||||||||||
| Direct prerequisites – Weak prerequisite | none | ||||||||||||
| Direct prerequisites – Parallel prerequisite | none | ||||||||||||
| Direct prerequisites – Milestone prerequisite | none | ||||||||||||
| Direct prerequisites – Exclusion | none |
Objectives
Programme
Detailed topics of lectures
1. Motivations. The potential of quantum computing. Quantum mechanics basics.
2. Postulates of quantum computing: quantum bits, operations, measurement, register. Entanglement and its effects.
3. Bell states. EPR paradox. Measurement techniques: projective and POVM measurement.
4. Fundamentals of quantum computing (No Cloning Theorem, generation of superposition quantum bits, quantum parallelism). Design methodology of quantum algorithms.
5. Quantum computing algorithms: database management (finding a given element, finding the optimum, reducing error probability)
6. Quantum computing algorithms: quantum Fourier transform, order search, Shor algorithm
7. Post-quantum cryptography
8. Overview of physical architectures and current implementations of quantum computers
9. Implementation challenges of quantum hardware (quantum bits, quantum gate error correction)
10. Complexity problem class of quantum computers
11. Quantum computing: benchmarking
12. Programming quantum computers
13. Quantum artificial intelligence
14. End of semester summary. Outlook: the market and future of quantum computers
Detailed topics for exercises/labs
1. Operations with quantum bits and quantum registers (tensor multiplication)
2. Design of quantum information algorithms (construction exercise)
3. Decomposition: reduction of unitary transforms to elementary gates (practical example: quantum Fourier transform)
4. Statistical testing of quantum random numbers
5. Handling quantum bits with quantum computers of different architectures
6. Complex quantum algorithms
7. Next generation quantum computers
1. Motivations. The potential of quantum computing. Quantum mechanics basics.
2. Postulates of quantum computing: quantum bits, operations, measurement, register. Entanglement and its effects.
3. Bell states. EPR paradox. Measurement techniques: projective and POVM measurement.
4. Fundamentals of quantum computing (No Cloning Theorem, generation of superposition quantum bits, quantum parallelism). Design methodology of quantum algorithms.
5. Quantum computing algorithms: database management (finding a given element, finding the optimum, reducing error probability)
6. Quantum computing algorithms: quantum Fourier transform, order search, Shor algorithm
7. Post-quantum cryptography
8. Overview of physical architectures and current implementations of quantum computers
9. Implementation challenges of quantum hardware (quantum bits, quantum gate error correction)
10. Complexity problem class of quantum computers
11. Quantum computing: benchmarking
12. Programming quantum computers
13. Quantum artificial intelligence
14. End of semester summary. Outlook: the market and future of quantum computers
Detailed topics for exercises/labs
1. Operations with quantum bits and quantum registers (tensor multiplication)
2. Design of quantum information algorithms (construction exercise)
3. Decomposition: reduction of unitary transforms to elementary gates (practical example: quantum Fourier transform)
4. Statistical testing of quantum random numbers
5. Handling quantum bits with quantum computers of different architectures
6. Complex quantum algorithms
7. Next generation quantum computers
The main objectives of the course are to provide knowledge on the operation and programming of quantum computers. In this context, students will become familiar with the different quantum computer architectures. On the other hand, the design methodology of quantum algorithms and the most important efficient algorithms will be presented, as well as the state-of-the-art quantum computer programming languages and systems that allow them to run on quantum computers. Finally, students will be introduced to benchmarking techniques to qualify quantum computing systems.
Learning outcomes
Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:
Knowledge
No learning outcomes recorded.
Skills
No learning outcomes recorded.
Attitudes
No learning outcomes recorded.
Autonomy and responsibility
No learning outcomes recorded.
Oktatási módszertan
Lecture. Successful completion of the subject and the interdependence of knowledge require to continuous follow the content of the lectures.
Practice: review of lecture material, supplemented by practical examples.
Tanulástámogató anyagok
Online források
S. Imre, F. Balázs: Quantum Computing and Communications – An Engineering Approach, Published by John Wiley and Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, 2005, ISBN 0-470-86902-X, 283 oldal; Additional Hungarian and English language resources are available in electronic form.
Recommended preliminary knowledge for completing the subject
Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
probability, linear algebra
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
probability, linear algebra
General rules
Requirements:
During the semester, students write 1 mid-term exam and 2 small homework assignments. The criteria for the successful semester: minimum of 40% of the score of the mid-term exam AND minimum of 40% of the total score of the two small assignments.
Oral exam
Additional possibilities:
Students will be given the opportunity to retake the mid-term exam during the retake week.
Late submission of the two small homework assignments is possible until the fourth day of the retake week for a special fee.
Assessment methods
In-term assessments
No detailed assessments provided.
Weight of in-term assessments
No weights provided.
Exam-period assessments
No detailed assessments provided.
Weight of exam elements
No weights provided.
Grade calculation
No grade thresholds provided.
Attendance requirements
No attendance requirements provided.
Rules for retake and resubmission
Not provided.
Short description
Not provided.
Detailed description
Not provided.
Recommended courses
Not provided.
Workload to complete the subject
No workload breakdown provided.
Validity of subject requirements
Requirements valid from:
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Requirements valid until:
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Curriculum placement
No curriculum placements recorded for this subject version.