Details
Introduction:
Quantum computing has enormous possibilities in terms of its potential computing power, but ensuring that quantum software is robust is a difficult problem. This project will look to tackle the problem of quantum “flakiness” on two fronts: (i) develop software solutions that have an in-built capacity to be robust to potential circuitry “noise”, and (ii) development of techniques to assess quantum software robustness through more accurate software tests.
About the project:
Quantum circuits are highly prone to noise, and for quantum computing to be a successful paradigm we need techniques to address its potential “flakiness”. While quantum error correction schemes have gone some way to ensure the reliability of quantum computations, they require more resources in terms of precious qubits.
In this project, we will take an alternative, two-pronged approach. The first part will apply search-based techniques (including stochastic optimization algorithms) to evolve quantum circuits that have an in-built robustness to typical circuitry noise. Secondly, we need to be able to differentiate between faults and regular non-determinism in quantum circuits. As such, we will investigate how to generate test suites that accurately assess software quality, avoiding the problem of flaky software tests. We will tackle this by applying techniques from machine learning and established research on flakiness for regular software.
Interested applicants are advised to contact Phil McMinn ([email protected]) to discuss more details.
Supervisor Bio:
The lead supervisors for this project are Professors Phil McMinn and John Clark. Professor Phil McMinn is an expert in software testing, and applying search-based techniques (including evolutionary algorithms) to problems in software engineering. Professor John Clark is an expert in quantum computation, security, and software engineering.
About the Department & Research Group:
You will be a part of the vibrant and highly social software testing research group, which is made up of 13 other PhD students and post-doctoral researchers supervised by different academics in the group. In the Department of Computer Science at Sheffield, 99% of our research was rated in the highest two categories in the REF 2021, meaning it was classed as world-leading or internationally excellent. We were also ranked 8th nationally for the quality of our research environment.
Candidate Requirements
We require a 1st or 2:1 in a computing degree.
Information on the English language requirements can be found here: https://www.sheffield.ac.uk/postgraduate/english-language.
How to apply
To apply for a PhD studentship, applications must be made directly to the University of Sheffield using the Postgraduate Online Application Form. Make sure you name Phil McMinn as your proposed supervisor.
Information on what documents are required and a link to the application form can be found here -
https://www.sheffield.ac.uk/postgraduate/phd/apply/applying
Your application needs to include a research proposal that:
- outlines your reasons for applying for this studentship
- explains any details of your skills and experience in the topic areas
- gives any initial ideas you have on how to tackle the project.
Funding Notes
This PhD studentship will cover standard UK home tuition fees and provide a tax-free stipend at the standard UKRI rate (currently £18,622 for 2023/24) for 3.5 years. If you are an overseas student, you are eligible to apply but you must have the means to pay the difference between the UK and overseas tuition fees by securing additional funding or self-funding. Further information on International fees can be found here - https://www.sheffield.ac.uk/new-students/tuition-fees/fees-lookup