CDT Student Interviews – Spotlight on Conor McPartland
In October 2020, LIV.DAT welcomed its 4th cohort of students into the Centre. Since they started their PhD’s, we have asked them a few questions as part of the CDT Spotlight Interview series. This will give you a more personal insight into work, motivation and challenges of our new students. Be sure to have a look at their personal profiles as well.
For this interview we have spoken with Conor McPartland, who will be searching for charged lepton-flavour violating tau decays to 3 muons with data taken from the ATLAS Experiment. Large samples of tau leptons are produced in the decay of heavy flavour hadrons and W bosons and both channels will be investigated. Using state-of-the-art analysis methods including machine learning methods, these channels together will provide a world-leading sensitivity exceeding the current limits. If no such decay is discovered new, more stringent limits, should be able to be set.
Why are you interested in Physics?
“One of the things that most excites me about physics is that so much is still being discovered, and that new discoveries often then lead to new and interesting questions. I also like the fact that physics is a very collaborative subject with many theories built upon each other.”
How did you end up in Liverpool?
“Liverpool is where I was born and grew up. I did my undergraduate studies here and enjoyed the course so decided to pursue doing a PhD here.”
Which contribution to your field do you consider to be the most significant?
“One of the great things about physics is how collaborative a subject it is, with many of the contributions being built upon one another. This makes it very difficult to choose the most significant contribution. One of the most significant has to be special relativity, but quantum field theory is also very significant. Without both of these, the standard model of particle physics wouldn’t exist, which is one of the most accurate models ever developed.”
What do you hope to contribute to your field?
“I hope to contribute my love of problem solving and hopefully, in the longer term, a knowledge of machine learning and other Big Data techniques.”
Where do you hope to end up after your PhD?
“As I’ve only started my PhD this year I haven’t given this a great deal of thought but I hope to end up somewhere in academia, or even in industry if I can continue using my problem solving and data analysis skills.”
Why do you think Big Data is important?
“The Large Hadron Collider at CERN produces approximately 30,000TB of data a year which obviously would be impossible to fully search through using traditional data analysis techniques. Using big data techniques, it is possible to reduce this immense amount of data down to a more manageable amount, containing only possible signal events. Even once the data has been reduced, machine learning can be used to reduce the background to signal ratio, making analysis easier. Without big data techniques, a large amount of time would be spent combing through stacks of data to find possible signal events, which now can be achieved relatively quickly, leaving more time for analysis.”