# INTRODUCTION TO QUANTUM COMPUTING - 2024/5

Module code: PHYM066

## Module Overview

Quantum Computing relies on Quantum Physics, naturally, but you do not need to be fully trained as a physicist to be able to produce a quantum computer program. There are, however, some essential but very un-intuitive concepts that you would not normally have met if you have not already become an expert in quantum physics. This module is designed to give an intensive introduction to those concepts. You will not become an expert in quantum physics, but after this module you will understand how to use it for the purpose of processing quantum information.

### Module provider

Mathematics & Physics

### Module Leader

MURDIN Benedict (Maths & Phys)

### Number of Credits: 15

### ECTS Credits: 7.5

### Framework: FHEQ Level 7

### Module cap (Maximum number of students): N/A

## Overall student workload

Independent Learning Hours: 75

Lecture Hours: 20

Tutorial Hours: 10

Guided Learning: 40

Captured Content: 5

## Module Availability

Semester 2

## Prerequisites / Co-requisites

N/A

## Module content

**Classical information vs quantum information. **

The fundamental building blocks of classical computers are switches (transistors) that can be on or off, and they are connected together in such a way that they can perform classical (Boolean) logic. These logic circuits are connected together to produce more sophisticated operations of machine language, which are used to make assembly language and ultimately higher programming code. In order to understand the building blocks of a quantum computer, we first need to explore traditional Boolean logic, and some background mathematical concepts like complex numbers and vectors (often written in what is called Dirac notation).

**Quantum operators and quantum measurement**

Quantum information has a very unusual property that it changes when you look at it. Fortunately (or unfortunately depending on how you look at it) your everyday experience is much simpler so that if you look at a train going past and then you look away, you can be pretty sure of what is going to happen next. In this unit we will delve into the concept of superpositions, where the system can be in two states at once, what happens when you observe a superposition, I.e. quantum measurement a.k.a. wavefunction collapse, and how to do some simple quantum operations and quantum logic before the collapse.

**Linear algebra **

Before moving to more complicated operations we need some more mathematical tools from linear algebra, which will help us describe larger superposition states.

**Multiple qubits and circuits**

Now we have all the tools needed to think about the spookiest of quantum ideas: action at a distance caused by entanglement. The idea that an action on something has an action on something else when there is no present connection and no exchange of information is a little mind-bending, but in this unit we will make use this property to build some multi-qubit gates and elementary quantum circuits. We will end by looking at the famous Deutch algorithm that demonstrates quantum speedup relative to a classical algorithm to do the same thing.

## Assessment pattern

Assessment type | Unit of assessment | Weighting |
---|---|---|

School-timetabled exam/test | In-Class Test Invigilated (1hr30mins) | 30 |

Coursework | Skills reflection | 20 |

Examination | Exam (1hr30mins) | 50 |

## Alternative Assessment

N/A

## Assessment Strategy

The __assessment strategy__ is designed to provide students with the opportunity to demonstrate

- analytical ability by solution of unseen problems
- subject knowledge by recall of theoretical results
- practical skill by generation of e.g. elementary quantum circuits for simple functions
- self-reflection on weaknesses and skills

Thus, the

__summative assessment__for this module consists of:

- an in-class test for demonstration of knowledge and cognitive skills in the mathematical machinery of quantum computing (Learning Outcomes 1-4)
- a self-reflection on the weakest area of skills coursework
- an exam for demonstration of skill in problem solving and synthesis of both machinery and concepts (Learning Outcomes 5-7)

**Formative assessment:**

- An on-line quiz will follow every lecture to reinforce content and allow students to gauge their own progress
- As preparation for the exam, tutorials will include examples of exam-style and/or past paper questions, followed later by model solutions.

**Feedback:**

- The online quiz above will provide instant feedback.
- Students will receive verbal feedback on progress with problems in tutorials and model solutions to the tutorial questions.

## Module aims

- This module aims to introduce fundamental concepts relating to quantum computing, to enable those without any prior undergraduate training in quantum physics to access more advanced content in quantum computing later in the course.
- It aims to provide a revision for physics graduates and a primer for graduates in other disciplines, and ensure that important notation and background required is understood in the same way by all.

## Learning outcomes

Attributes Developed | ||

001 | Compare and contrast the information content of a classical register of bits with a quantum register of qubits. | KC |

002 | Explain difference between measurement of classical and quantum measurement and the dependence on the basis choice. | KC |

003 | Apply operators corresponding to common quantum gates to quantum statevectors to produce new qubit states. | C |

004 | Find the eigenvectors of a matrix operator and explain their utility/importance in quantum computing. | C |

005 | Explain the difference between an entangled state and a product state, and describe operators that can produce interchange of one with the other. | KC |

006 | Theorize or generalize in unseen situations where quantum qubit gates are applied. | C |

007 | Generate simple qubit circuits. | C |

Attributes Developed

**C** - Cognitive/analytical

**K** - Subject knowledge

**T** - Transferable skills

**P** - Professional/Practical skills

## Methods of Teaching / Learning

The __learning and teaching__ strategy is designed to provide:

- An introduction to the theoretical framework behind the necessary quantum physics to practical quantum computing
- practice in problem solving to develop the cognitive skills

The

__learning and teaching__methods include:

- interactive lectures backed up with guided study to stimulate uptake of subject knowledge
- tutorial demonstration of solutions to key problems, with practice for students both before and after having attempted them for formative feedback
- MOOC attendance for basic skills development – a choice of three courses based on the self-reflection coursework.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

## Reading list

https://readinglists.surrey.ac.uk

Upon accessing the reading list, please search for the module using the module code: **PHYM066**

## Other information

**Digital Capabilities: **In this module we study the basics of a revolution in digital capabilities: the quantum computer.

**Resourcefulness and Resilience**: The self-reflection coursework will allow students to demonstrate self-reliance and ability to take charge of their own education strategy, and their approach to remedying weakness and to attain strength.

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2024/5 academic year.