Regarding the current health situation, keep track of the university and cantonal guidelines. An online alternative will be provided for all lectures. Information will be sent by email.

The course begins on 22nd Feb 2022 and will have weekly lectures and exercises.

Course Content

Quantum information theory is the basis of multiple emerging technologies, such as quantum computation and quantum crypotography. It allows us to understand how quantum effects in physical systems may be harnessed for new forms of information processing. The course will also feature some hands on experience with quantum technology, via the open-source Qiskit framework for quantum computing.

Course Text

The course will be based on the Qiskit textbook.

Lectures

In-person lectures will be held when possible. However, since the lectures will follow the same format as in 2021, pre-recorded lectures will be available for all who cannot attend for any reason.

Lecture 1, March 1: The Atoms of Computation and What is Quantum
Lecture 2, March 8: Python, Qiskit and Hello Qiskit
Lecture 3, March 15: Representing Single Qubit States and Gates
Lecture 4, March 22: Multi-qubit States and Circuit Identities
Lecture 5, March 29: Fun with Matrices
Lecture 6, April 5: Circuits and Universality
Lecture 7, April 12: Basic Algorithms and Protocols
Lecture 8, April 19: From the Fourier Transform to Shor's Algorithm
Lecture 9, April 26: Grover's Algorithm (and why we can't yet run it)
Lecture 10, May 3: Introduction to Quantum Error Correction
Lecture 11, May 10: Quantum Error Correction: Surface Codes
Lecture 12, May 17: Quantum Games
Lecture 13, May 24: tbc
Lecture 14, May 31: tbc

Exercises

Some exercises will be in the form of Jupyter notebooks. These can be run locally by installing Python 3, Jupyter and Qiskit. They can also be run online without any installation using the IBM Quantum Lab. When you are on the files menu of the lab, you can click on the 'upload file' icon to upload notebooks.

The easiest way to to download the exercises is to download the whole repository using this link.

The exercises will make up 50% of the final grade. On each of the exercises you can score a value between 0 and 1, where 1 is the best score.

Exercises are due on Tuesdays at 4:15pm and can be handed it as a hand-written piece of paper or via email to the corresponding teaching assistant (TA). If the exercise is a python notebook (.ipynb file), please send the .ipynb file as well as a pdf-version of that file by email.

The TAs of this course are Maria (maria.spethmann@unibas.ch), Bence (bence.hetenyi@unibas.ch), Pierre (pierre.fromholz@unibas.ch) and Even (even.thingstad@unibas.ch).

Here is the provisional list with the due dates for all exercises and the corresponding TAs:

Exercise 1, due on March 15, hand in to Maria
Exercise 2, due on March 22, hand in to Bence
Exercise 3, due on March 29, hand in to Pierre
Exercise 4, due on April 05, hand in to Pierre
Exercise 5, due on April 12, hand in to Even
Exercise 6, due on April 19, hand in to Even
Exercise 7, due on April 26, hand in to Bence
Exercise 8, due on May 03, hand in to Maria
Exercise 9, due on May 10, hand in to Maria
Exercise 10, due on May 17, hand in to Pierre
Exercise 11, due on May 24, hand in to Even
Exercise 12, due on May 31, hand in to Bence

The solutions of the exercises are presented at the exercise course a week after. Further, the TAs will give a few hints about the next exercise. If you cannot come to the exercise but would like to know the hints, please send an email to the corresponding TA.

Exam/Final Project

In 2020 and 2021, the course had a final project instead of an exam. Whether we'll do the same in 2022, or have an exam instead, has not yet been decided.