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Aims:

The aim of the module is to introduce the students to the principles of quantum mechanics from a computer science perspective, and to the field of quantum computation and algorithms.

Intended learning outcomes:

On successful completion of the module, a student will be able to:

1. Understand (i.e., be able to describe, analyse and reason about) quantum computation, and how it differs from classical probabilistic computation.
2. Analyse the behaviour of simple quantum circuits.
3. Understand how quantum superposition and interference can give quantum speedups over classical algorithms in certain cases and apply these concepts to the design of quantum algorithms.
4. Derive the Quantum Fourier Transform, and apply it to the design of quantum algorithms
5. Derive Grover’s unstructured search technique and apply it to the design of quantum algorithms.

Indicative content:

The module provides a first course on quantum computation. The following is indicative of the topics the module will typically cover:

The basic mathematical formalism of quantum mechanics is be introduced from a computer science perspective, assuming no prior knowledge of quantum mechanics or physics. Building on this, the module develops the standard circuit model of quantum computation and basic quantum complexity theory. Most of the module is devoted to quantum algorithms, including rigorous derivations and algorithm analysis. This section of the course starts from simple examples, and builds up to the major quantum algorithms, such as Shor’s quantum factoring algorithm and Grover’s unstructured search algorithm.

Requisites:

To be eligible to select this module as an optional or elective, a student must be registered on a programme and year of study for which it is a formally available.