Introduction to Quantum Information Processing

QIC 710, CS 768, CO 681, PHYS 767, AMATH 871, PMATH 871 (Fall 2023)

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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 four parts:

- A basic introduction, to the quantum information framework that is intended to be accessible to absolute beginners.
- Quantum algorithms, including black-box algorithms, 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, entropy and noiseless coding, error-correcting codes and fault-tolerance, and non-locality.
- Quantum cryptography, including an overview of the Bennett-Brassard key exchange protocol (BB84), and the Lo-Chau key exchange protocol, and an analysis of the problem of bit commitment.

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

5 assignments 12% each

1 project 40%

References

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 7:46 Correction: in 2023, there are 5 assignments, worth 12% each