FDD3280 Quantum Computing for Computer Scientists 7.5 credits

The course is organized into two modules: 1) The mathematics and physics of quantum computing 2) The making of quantum computing. The first module introduces complex numbers, complex vector spaces, the leap from the classical world to the quantum world, and provides an introduction to basic quantum theory. The second module discusses architectures, algorithms, programming apporaches and hardware for quantum computing.

The course activities include lectures, readings, quizzes, assignments and a final project. 

The course is organized into two modules. We first learn about the mathematics and physics of quantum computing by introducing complex numbers, complex vector spaces, the leap from the classical world to the quantum world, basic quantum theory. The second module discusses architectures, algorithms, programming approaches, and hardware for quantum computing.

After the successful completion of the course, the student will be able to:

• Describe the role of complex numbers and complex vector spaces in quantum computing
• Describe superposition of state, non-locality effects, probabilistic laws
• Compare classical computing to quantum computing in terms of advantages and disadvantages
• Generalize the concept of bit, classical gate, and registers to qubit, quantum gates and quantum registers
• List, formulate and describe key algorithms in quantum computing
• Develop a quantum computer emulator
• Describe the hardware realization of quantum computing

Knowledge of linear algebra, Python or Matlab is required.

Knowledge of linear algebra, Python, or Matlab is required.

A laptop or a workstation is necessary to complete the assignments and the final project.

The course textbook is Yanofsky, Noson S., and Mirco A. Mannucci. Quantum computing for computer scientists. Cambridge University Press, 2008. An additional reference book for the course is Loredo R. Learn Quantum Computing with Python and IBM Quantum Experience: A hands-on introduction to quantum computing and writing your own quantum programs with Python. Packt Publishing Ltd; 2020 Sep 28.

If the course is discontinued, students may request to be examined during the following two academic years.

• EXA1 - Examination, 7.5 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

In order to pass the course, the student must pass two assignments and one final course project.

Stefano Markidis

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.