Quantum Information Theory - M1 - 8EC

Prerequisites

Strong command of linear algebra (in finite dimensions) and familiarity with probability theory (with finitely many outcomes) is required. Concretely this means the material in Chapter 2.1 and Appendix 1 of "Quantum Computation and Quantum Information" by Nielsen and Chuang. For a more formal account, see Sections 1.1 and 1.2.2 of "Theory of Quantum Information" by Watrous. Please have a brief look at last year's lecture notes to get more of an impression. In addition, you should have experience writing down correct and complete mathematical proofs. We will offer some optional homework that will involve programming to explore mathematical concepts that we discuss in class. You can use any programming language of your choice. Prior exposure to quantum mechanics or information theory can be very helpful, but is not necessary to follow the course.

Aim of the course

With the birth of Quantum Mechanics a century ago, our understanding of the physical world has profoundly expanded, and so has our understanding of information. While a classical bit assumes only discrete values, represented by the binary values zero and one, a quantum-mechanical bit or "qubit" can assume a continuum of intermediate states. Quantum Information Theory studies the remarkable properties of this new type of information, ways of processing it, as well as its advantages and limitations.

This course offers a mathematical introduction to Quantum Information Theory. We will start with the fundamentals - namely, quantum states, measurements, and channels - and then discuss some more advanced topics such as compression of quantum information and entanglement theory).

This course complements Ronald de Wolf's course "Quantum Computing". Students interested in writing a master's thesis in quantum information/computing are encouraged to follow both courses.

Video recordings

TAs

Lecturers

Rules about Homework/Exam

There will be a written exam at the end of the course. The final grade will be determined by the following formula:

60% exam grade + 40% homework grade

with the lowest homework grade being ignored when computing the average. In addition, your exam grade has to be at least a 5.0. The same rules applies for the retake exam.

There will be bi-weekly homework problems, announced on the course homepage. You must submit your completed homework on ELO in 2 weeks before the start of the lecture. Assignments will be accepted late only if you have extenuating circumstances (such as sickness or family emergency) and provided you confirm with a TA or lecturer before the deadline.

You are allowed to bring one self-prepared "cheat sheet" to the exam (A4 paper, hand-written, you can use both sides).

Lecture Notes/Literature

Most relevant to this course:

Supplementary literature: