PhD project: Use of machine learning in the ATLAS trigger
Supervisor: Prof Mario Campanelli
The trigger of the ATLAS experiment is a very complex system combining ultra-high speed electronics and parallel software to select about 2000 collisions out of the 40 millions produced every second by the LHC. The current system is constantly upgraded and improved to deal with the ever increasing challenges of data-taking. For the High-Luminosity LHC, the first trigger level will be entirely re-designed and will make much more use of dedicated firmware. So far the use of Machine Learning on the Atlas trigger has been limited to some specific final states, but it is rapidly growing. This project will consist in the application of Machine Learning on the current trigger systems, especially for jets and low-energy interactions, and on the future system being designed for the high-Luminosity LHC. The analysis part of the project will be based on the use of Machine Learning on the identification of W bosons, and the measurement of WW production for events where the original protons are intact and measured by forward detectors.
More details on ATLAS at UCL can be found here.
For more details please contact m.campanelli at ucl.ac.uk