Introduction to Quantum Information Processing
QIC 710, CS 768, CO 681, PHYS 767, AMATH 871, PMATH 871 (Fall 2025)
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General course information
The objective of this course is to introduce the mathematical theory of quantum information processing (a.k.a. quantum computing) at the graduate level.
The course consists of three parts:
- A primer for beginners: a basic introduction, to the quantum information framework that is intended to be accessible to absolute beginners.
- Quantum algorithms: including black-box algorithms, Fourier transform, Shor’s algorithms for discrete log and factoring, and Grover’s search algorithm.
- Quantum information theory: including density matrices and quantum operations on them, distance measures between quantum states, Schmidt decomposition, error-correcting codes, and non-locality.
If time permits, some topics from noiseless compression, to quantum cryptography may also be covered.
A more detailed course syllabus [pdf]
Intended audience
This course is mainly intended for graduate students in these departments/schools: Computer Science, Combinatorics and Optimization, Physics and Astronomy, Applied Mathematics, and Pure Mathematics. Other students may take this course with the permission of the instructor. Prerequisites are MATH 235 or equivalent (e.g. PHYS 364 & 365); STAT 230 or equivalent.
Evaluation
6 assignments 10% each
2 tests 20% each
References
- Quantum Information Processing (lecture notes) [here]
- Quantum Information Processing (videos from 2020) [here]
Additional (optional) references
- An Introduction to Quantum Computation, P. Kaye, R. Laflamme, M. Mosca (Oxford University Press, 2007).
- Quantum Computation and Quantum Information, Michael A. Nielsen and Isaac L. Chuang (Cambridge University Press, 2000).
A brief overview video (from 2020)
Duration 7:09 (5:43 at 1.25 speed)