Quantum Computers

Learning Outcomes

  1. explain the principles of quantum mechanics
  2. apply Dirac notation in simple calculations in quantum mechanics
  3. identify the state of the quantum bit on the Bloch sphere
  4. describe the quantum key distribution protocol BB84
  5. explain entanglement in a qantum systems
  6. describe the Deutsch and Shor quantum algorythms
  7. outline the basic features of candidate technologies for physical realization of quantum computers

Forms of Teaching

Lectures

Exercises

Partial e-learning

Week by Week Schedule

  1. Classical vs; Quantum Mechanics; Qubit states and light polarization; Measurement.
  2. Linear and circular polarisation; Amplitude and measurement; Dirac bra i ket notation; Transition amplitudes.
  3. Linear operators and vector spaces; Basis of a vector space.
  4. Represenatation of an operator in a basis; Diagonalisation of an operator; Eigenvalues and eigenfunctions.
  5. Classical cryptography; Quantum cryptography.
  6. Schroedinger equation and quantum mechanical postulates; Two levels quantum systems.
  7. Bloch sphere; Entangled states; Pure and mixed states; Density matrix; Multi qubit states.
  8. Midterm exam.
  9. Classical reversible gates; Unitary transformations; Toffoli gate; Fredkin gate; Pauli gates; Walsh-Hadamard gate; Controlled gates; Universal quantum gates; Quantum Fourier transform.
  10. Quantum algorithm; Deutsch algorithm; Deutsch-Jozsa algorithm.
  11. Grover algorithm; Shore algorithm.
  12. Dense coding; Teleportation.
  13. DiVincenzo criteria ; NMR quantum computer; Trapped ions; Neutral atoms.
  14. Josephson junction qubits; Quantum dots.
  15. Final exam.

Study Programmes

University undergraduate
Computing (study)
Elective Courses (5. semester)
Electrical Engineering and Information Technology (study)
Elective Courses (5. semester)
University graduate
Computer Engineering (profile)
Mathematics and Science (1. semester)
Computer Science (profile)
Mathematics and Science (1. semester)
Control Engineering and Automation (profile)
Mathematics and Science (1. semester)
Electrical Engineering Systems and Technologies (profile)
Mathematics and Science (1. semester)
Electrical Power Engineering (profile)
Mathematics and Science (1. semester)
Electronic and Computer Engineering (profile)
Mathematics and Science (1. semester)
Electronics (profile)
Mathematics and Science (1. semester)
Information Processing (profile)
Mathematics and Science (1. semester)
Software Engineering and Information Systems (profile)
Mathematics and Science (1. semester)
Telecommunication and Informatics (profile)
Mathematics and Science (1. semester)
Wireless Technologies (profile)
Mathematics and Science (1. semester)

Literature

(.), S. Ilijić, Kvantna računala: fizika, informacija i algoritmi (skripta), FER, 2018. (u pripremi),
(.), N.D. Mermin, Quantum Computer Science: An Introduction, Cambridge University Press, 2007, URL: http://www.lassp.cornell.edu/mermin/qcomp/CS483.html,
(.), R.P. Feynman, R.B. Leighton, M. Sands, The Feynman Lectures on Physics, Volume III: Quantum Mechanics, Addison Wesley, 1965, URL: http://www.feynmanlectures.info,
(.), Michel Le Bellac, A Short Introduction to Quantum Information and Quantum Computation, Cambridge University Press, 2006.,
(.), Michel Le Bellac, Quantum Physics, Cambridge University Press, 2006.,
(.), Roman Axler, Linear Algebra Done Right, 2nd ed., Springer, 1997.,

General

ID 183402
  Winter semester
5 ECTS
L3 English Level
L1 e-Learning
45 Lectures
15 Exercises
0 Laboratory exercises
0 Project laboratory