Research Group: Particle Physics Research Centre Length of Study in Years: 4 years Full-time Project: yes
Funding is provided via the China Scholarship Council.
The Weak Mixing Angle (WMA) is a fundamental parameter of the Standard Model of Particle Physics. It describes the mixing between the W and Z boson fields and is closely related to the masses of the W and Z particles. The previous generation of WMA measurements yielded a longstanding discrepancy of more than 3 standard deviations between two renowned experiments (LEP at CERN and SLD in the USA). In 2022 the ElectroWeak sector of the Standard Model was shaken by the publication of a highly precise measurement of the W boson mass found to be incompatible with theoretical predictions. If confirmed, this would indicate the clear existence of new exotic physics. Therefore there is great international attention on new high precision measurements of the WMA, which may see similar deviations from theoretical predictions.
Using a large data set of proton-proton collisions recorded between 2015 and 2025 the ATLAS experiment at the Large Hadron Collider is expected to reach the world’s most precise measurement of the WMA. The focus will be on measuring Z bosons decaying to electron-positron pairs very close to the forward beampipe. This is an experimentally challenging region with high backgrounds but where the measurement has maximum sensitivity to the WMA.
The project will use a novel method to extract the WMA developed by Prof Rizvi [JHEP 12 (2017) 059]. It uses a state-of-the-art unfolding techniques to correct for detector effects. An advanced profile likelihood fit to simultaneously determine the WMA and the Parton Density Functions (PDFs). This will minimise the largest uncertainty arising from the PDFs – an area where Prof Rizvi has considerable expertise. The method will be applied to a much larger dataset and is anticipated to achieve a precision of better than 26 x 10-5. This will be the world’s most precise measurement from a single experiment.
A comprehensive training programme is offered involving 150 hours of lecture courses in particle physics and detection methods, a 2-weeek residential summer school, and attendance at an international conference to present your work towards the end of the PhD. Students may also participate in the DISCnet training programme in machine learning, or have the opportunity to spend 6-12 months based at CERN, in Geneva depending on funding.
The project will be supervised by Prof Rizvi who has an established expertise in machine learning and operating the Level-1 Calorimeter Trigger. He leads the ATLAS group at Queen Mary University of London, and has successfully supervised 15 PhD students, and currently leads two Centres for Doctoral Training in Data-Centric Engineering and in Data-Intensive Science for Particle Physics. He is a Fellow of the Alan Turing Institute – the national centre for Artificial Intelligence.
Supervisor Contact Details:
For more information on this project please contact Eram Rizvi (e.rizvi@qmul.ac.uk).
Deadline - 29th of January 2025
Application Method:
To apply for this studentship please select September entry in the following page:
https://www.qmul.ac.uk/postgraduate/research/subjects/physics.html
SPCS Academics: Professor Eram Rizvi