NDAK24010U Quantum Error Correction (QEC)

Volume 2024/2025
Content

The course will cover the basic theory of quantum error correction and fault-tolerance, including the following specific topics:

  1. Basics of classical coding theory, parity check matrices, tanner graphs 
  2. Basic quantum codes: Shor code, concatenation codes
  3. QEC theory: Knill Laflemme conditions, Gottesman Knill theorem, threshold theorem, 
  4. Topological codes: the toric code, color code. 
  5. Decoding algorithms (mostly for the color code) 
  6. Fault tolerance: Lattice surgery, and magic state injection. 
  7. Fault-tolerant photonic quantum computing
  8. (If time permits) Advanced topics: LDPC codes, self correction, bosonic codes
Learning Outcome

Knowledge:

  • Describe and design quantum error correction codes
  • Describe and design fault-tolerant architectures for quantum computing 

 

Skills:

  • Perform resource estimates based on specific QEC architectures.
  • Design of decoders for topological codes

 

Competences:

  • Ability to work on state of the art topics in quantum error correction, and read research publications on the topic. 
Literature

The teaching material will be gathered from various sources, including: 

  • Personal set of lecture notes
  • Various review articles
Bachelor in Mathematics, Physics or Computer Science

Academic qualifications equivalent to a BSc degree is recommended.

You should have passed the courses NFYK23002U Introduction to Quantum Information Science & NMAK23007U Introduction to Quantum Computing or similar course before registering for this course.
Lectures and exercises
  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 160
  • Exercises
  • 14
  • Exam
  • 4
  • Total
  • 206
Continuous feedback during the course of the semester
Credit
7,5 ECTS
Type of assessment
On-site written exam, 4 hours under invigilation
Aid
Only certain aids allowed
  • Books
  • Notes
  • Calculator
Marking scale
7-point grading scale
Censorship form
No external censorship
Re-exam

Same as the ordinary exam

Criteria for exam assesment

See Learning Outcome