Course content

One of the most exciting quantum technologies proposed is quantum computation, where information is coded in quantum bits (qubits), instead of classical bits. Since these qubits can be in a superposition of 0 and 1 and can be entangled with each other, a quantum computer could perform certain tasks exponentially faster than a regular computer, such as database searching and prime factorization. This advantage is expected to revolutionize fields ranging from cryptography and image recognition to quantum chemistry and drug development. This course presents an introduction to quantum information and computation, from a physicist's perspective. After reviewing the basic quantum mechanics and linear algebra needed to understand the qubit, we will discuss single- and two-qubit gates and show how they together offer universal quantum computation. We will exemplify the quantum advantage by combining these gates into different quantum algorithms, such as the Deutsch-Jozsa, phase estimation, and prime factorization algorithms. We then discuss the basics of quantum error correction, showing how it is possible to recover randomly occurring errors in the performance of an algorithm. Finally, we will connect the rather abstract ideas we developed so far to reality again, by investigating the physical working of several leading qubit platforms, including spin qubits and superconducting qubits.

Learning outcome

• A thorough understanding of the basics of quantum information and computation and insight in the essence of quantum advantage.
• A good overview of the most important quantum algorithms proposed and a deeper understanding of their workings.
• Conceptual understanding of quantum error correction.
• Insight in the physics of the leading qubit implementations.

Learning methods and activities

Lectures. Expected workload in the course is 225 hours.

Recommended previous knowledge

Very basic knowledge of quantum mechanics and linear algebra. Basic understanding of superconductivity and semiconductor physics is beneficial for the last part of the course, but not necessary.

Course materials

Lecture notes and powerpoint slides.