FYSS5403 Introduction to Quantum Computing (5 cr)

Study level:
Advanced studies
Grading scale:
0-5
Language:
English
Responsible organisation:
Department of Physics
Curriculum periods:
2020-2021, 2021-2022, 2022-2023

Description

  • Definition of quantum bits (qubits), quantum computation

  • Single- and two-qubit quantum gates and universal gate sets

  • Quantum parallelism and no-cloning theorem

  • Bell states and few-qubit algorithms (Quantum cryptography, Dense coding, Quantum teleportation)

  • Quantum algorithms providing the speedup over classical ones (Deutsch, Bernstein-Vazirani and Simon problems, Grover’s and Shor’s algorithms)

  • Quantum error correction, density operator and decoherence

  • Designing and implementing quantum programs using IBM Q Experience

  • Basic hardware components of different quantum computing platforms

  • State-of-the art and future of quantum computing 

Learning outcomes

After completion, the student understands the goals and methods of quantum computation and can design and implement quantum algorithms using IBM Q Experience online platform. The student is familiar with the material platform for qubit devises and gets the vision of recent developments in the field of quantum computing.

At the end of this course, students will be able to

  • Explain the difference between a quantum bit and a classical bit

  • Explain what are quantum computers

  • Describe single- and two-qubit quantum gates and universal gate sets

  • Explain what is Quantum cryptography, Dense coding and Quantum teleportation, and knows their mathematical underpinning

  • Name and explain quantum algorithms which provides the speedup over classical ones, such as Deutsch, Bernstein-Vazirani and Simon problems; Grover’s search algorithm and Shor’s factorization algorithm.

  • Explain the relation of Shor algorithm to the breaking of RSA encryption

  • Tell what are the qubit errors, why they are important and explain the basic approaches to quantum error correction

  • Design and run quantum programs on simulators and real devices using IBM Q Experience online platform and Qiskit developing framework

  • Describe basic hardware components of different quantum computing platforms 

Description of prerequisites

Linear algebra and basic quantum mechanics courses will be helpful but not necessary.

Study materials

  • Lecture slides, lecture notes, sample Python programs.
  • Online tutorials at https://qiskit.org/ 

Literature

  • Quantum Computer Science: An Introduction by N. David Mermin, Cambridge University Press, 2007
  • Quantum computing: From linear algebra to physical realizations by M. Nakahara and T. Ohmi, 2008, CRC Press
  • Nielsen&Chuang, Quantum Computing and Quantum Information, Cambridge University Press, 2000

Completion methods

Method 1

Description:
Given every other year during autumn term, starting 2020.
Evaluation criteria:
Exercises and group work (e.g. exercises 80 %, group work 20 %)
Time of teaching:
Period 1, Period 2
Select all marked parts
Parts of the completion methods
x

Teaching (5 cr)

Type:
Participation in teaching
Grading scale:
0-5
Evaluation criteria:
Exercises and group work (e.g. exercises 80 %, group work 20 %)
Language:
English
Study methods:
  • Lectures, exercises, group work.

  • Exercises and a group work on the projects based either on the experiments with qubit devices through IBM cloud or the literature survey. 

Teaching