2026/27 Taught Postgraduate Module Catalogue

PHAS5440M Advanced Quantum Information Theory

15 Credits Class Size: 15

Module manager: Dr David Jennings
Email: D.Jennings@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2026/27

Pre-requisite qualifications

A bachelor degree with a 2:1 (hons) in one of: · Physics; · Joint degrees containing substantial elements of physics or mathematics; · Natural sciences, as long as physics is covered in the course content; · Geophysics; · Mathematics. Knowledge of quantum physics/mechanics is required.

Co-requisites

PHAS5410M Quantum Information Science and Technology

This module is not approved as an Elective

Module summary

An in-depth exploration of key topics in quantum information theory, including quantum mixed states, channels, metrology, and computing. You'll gain the tools to engage with contemporary research literature and understand advanced algorithmic concepts. The module prepares you for cutting-edge work in quantum algorithms and theoretical quantum information science.

Objectives

This module provides a rigorous foundation in the core theoretical principles underpinning contemporary quantum information science. Drawing on modern techniques and frameworks that have emerged from cutting-edge research, the course develops a coherent and unifying perspective on the field. Students will acquire the advanced mathematical tools and abstract conceptual framework necessary to engage with current research literature and to undertake independent research in quantum information science.

Learning outcomes

On successful completion of the module students will be able to:

1. Perform or evaluate advanced theoretical techniques and calculations in Quantum Information Theory.

2. Apply a range of modern techniques to the study of Quantum Information Technologies.

3. Develop problem-solving skills, and apply information-theoretic abstractions to concrete quantum systems.

4. Read and engage modern research papers in quantum information science.

Skills Learning Outcomes

a) Perform probabilistic and statistical reasoning in the context of problem-solving tasks.

b) Collaborate and communicate effectively with peers on a common goal.

c) Evaluate and appreciate the importance of information technologies on the modern world.

Teaching Methods

Delivery type Number Length hours Student hours
Lecture 22 1 22
Practical 10 1 10
Private study hours 118
Total Contact hours 32
Total hours (100hr per 10 credits) 150

Private study

118 hours of Private Study Time.

Opportunities for Formative Feedback

Students will receive formative feedback through problem sheets designed to develop both technical fluency and conceptual understanding. Selected problems will be discussed in workshops, and common misconceptions addressed in class. Interactive elements during lectures (e.g. short derivations and concept-check questions) will provide immediate feedback on understanding. During class short show-of-hands quizzes will provide interactive feedback,

Reading List

Check the module area in Minerva for your reading list

Last updated: 30/04/2026

Errors, omissions, failed links etc should be notified to the Catalogue Team