Nytt tillvägagångssätt till beräkningen av avgörande multi-jet-bakgrund i högenergiforskning

On June 1, 2023, the Swedish Research Council decided on funds for international postdoc within natural and engineering sciences. The Department of Physics and Astronomy was granted SEK 3 450 000 for the period 2023-2026 for one project.

Read more about International postdoc within natural and engineering sciences 2023

Project title: Novel approach to the computation of crucial multi-jet background in high energy research
Main applicant: Timea Vitos, High Energy Physics
Grant amount: SEK 3 450 000 for the period 2023-2026

Among the most crucial aspects for detecting new physics of fundamental particles beyond the Standard Model at facilities such as the LHC at CERN, are accurate and efficient tools for the computation of the background. Multi-jet events (large number of sprays of strongly interacting particles in the final state) are dominating background events at the LHC. However, due to their complexity, current toolkits are not sufficient for the calculation of such processes. I propose a solution to this via the development of an improved MadGraph5 matrix-element generator which utilizes a truncation of the colour sum (the most time consuming part of the computation), resulting in fast and accurate computation of multi-jet events. First, I will implement such a framework and validate its accuracy with expertise input from the MadGraph5 community through UCLouvain. Second, this implementation will be improved, by moving to a higher precision in the perturbative framework, in collaboration with higher-order QCD expertise at Budapest ELTE. Finally, I will explore the need to include higher orders in the colour sum. The project will lead to a new version of the open-access MadGraph5, which will be in the long term primarily utilized for the experimental analyses performed at Uppsala. As this tool is used world-wide in high energy research, the new version will be accessible to all research groups, such that experimental data will be used more efficiently in extraction of new physics signals.