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Introduction To Quantum Computing

Public syllabus for 2025-2026

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Academic overview

Programme
CS
Period
Year 1, Semester 1
Credits
5
Weeks
14

Curriculum placement

Appears in study plans

CS (2025 - 2027) Year 1, Semester 1 Elective subject, group 1

Teaching team

Course coordinator
(none)
Seminar coordinators
Florin Roșu

Learning time distribution

Total
Curriculum Lecture Practice Total Weekly Lecture Practice
42 28 14 3 2 1
Exam hours
4
Individual Study Bibliography study Field study Homework Tutoring Others
83 30 23 23 3 0
Overall
125

Learning outcomes

Knowledge

  • Mastering the fundamental notions of quantum computing

Skills

  • Understanding the fundamental notions of quantum computing

Responsibility

  • Professional development and self-confidentiality in own capacities by the presence of the abilities for understanding and develop the solution of quantum computing problems

Online platform

(none)

Course content

Content Methods Obs
Introduction to Quantum  Computing (Complexity in  today's world. Why Quantum  Computing? Universal vs.  Adiabatic / annealing  Algorithms. Players Quantum supremacy) Discourse, conversation, illustration by examples 2h
Fundamentals of Quantum  Computing (Complex Hilbert  spaces. Postulates of quantum  mechanics. Qubitsa Gates. Universal Quantum Computing. The source of OC's power) Discourse, conversation, illustration by examples 2h
Superposition (Interference.  Amplitudes. States) Discourse, conversation, illustration by examples 2h
Entanglement (Entanglement  defined. Why is entanglement  powerful. Non-local games) Discourse, conversation, illustration by examples 2h
Introduction to quantum  algorithms (Oracles. Amplitude  amplification. QFT) Discourse, conversation, illustration by examples 2h
A simple algorithm: Deutsch Josza Discourse, conversation, illustration by examples 2h
Shor's algorithm Discourse, conversation, illustration by examples 2h
Grover's algorithm Discourse, conversation, illustration by examples 2h
Introducing quantum  annealing Discourse, conversation, illustration by examples 2h
Optimization problems:  QUBO and PUBO (Quadratic.  Unconstrained Binary  Optimization. Polinomyial  Unconstrained Binary. Optimization. Embedding  problems) Discourse, conversation, illustration by examples 2h
Quantum-inspired  algorithms (How quantum  computing influences classical  computing) Discourse, conversation, illustration by examples 2h
Building quantum computers (DiVincenzo criteria) Discourse, conversation, illustration by examples 2h
Quantum computing applied  in the real world (Security.  Machine Learning. Chemistry.  Materials science) Discourse, conversation, illustration by examples 2h
Quantum Computing Q&A ( Open session, students get to  ask any question about  Quantum Computing.) Discourse, conversation, illustration by examples 2h
...

Course bibliography

Lo, Hoi-Kwong, Tim Spiller, and Sandu Popescu. Introduction to quantum computation and information. World Scientific, 1998. Le Bellac, Michel. A short introduction to quantum information and quantum computation. Cambridge University Press, 2006 Kaye, Phillip, Raymond Laflamme, and Michele Mosca. An introduction to quantum computing. OUP Oxford, 2006.

Seminar content

Content Methods Obs
Introducing Q#. Complex  arithmetic and linear algebra  operations. Single and multiple  qubit operations Problem-based approach, dialogue, learning through collaboration 2h
Operations with quantum gates Superposition Problem-based approach, dialogue, learning through collaboration 2h
Quantum measurements Problem-based approach, dialogue, learning through collaboration 2h
Teleportation and superdense  encoding Problem-based approach, dialogue, learning through collaboration 2h
Algorithms: Deutsch-Josza and  Grover Problem-based approach, dialogue, learning through collaboration 2h
Quantum Key Distribution: BB84 Problem-based approach, dialogue, learning through collaboration 2h
Entanglement games: CHSH  (non-local game), GHZ, Mermin Peres Magic Square Problem-based approach, dialogue, learning through collaboration 2h
Bibliography: Same as above

Seminar bibliography

The content is in accordance with the structure of similar courses from other universities and covers the fundamental aspects necessary to become familiar with the issue of quantum computing. The skills offered by this discipline are necessary for an IT specialist to identify effective solutions to solve specific problems, regardless of the specific field of activity.

Corroboration

(none)

AI tools guidance

(none)

Evaluation and delivery

Activity Criteria Methods Percentage
C
  • Knowledge of problems and solutions associated with quantum computing applications.
  • Technical quiz OR course presentation
  • 50.0%
S
  • Implementation of small quantum computing project
  • Project presentation
  • 50.0%

Performance standards

Knowledge of the main concepts used in the quantum computing. Knowledge of problems and solutions associated with quantum computing applications. Ability to identify the building blocks of quantum computing The final mark is computed as weighted average of the marks corresponding to the components specified at 10.4 and 10.5. The exam is considered passed if the average is at least 5 (it is not required that each mark is at least 5). In each session of exams (including re-examinations) the mark is computed using the same rule. The student can be re-examined only for the components for which the current mark is smaller than 5, excepting the cases when the student asks to be re-examined .

Additional info

(none)