January 27, 2023
Congratulations to Henry Truong on completing his thesis titled "Machine learning high multiplicity matrix elements for electron-positron and hadron-hadron colliders"! The abstract of his thesis was:
The LHC is a large-scale particle collider experiment collecting vast
quantities of experimental data to study the fundamental particles, and forces, of
nature. Theoretical predictions made with the SM can be compared with observables
measured at experiments. These predictions rely on the use of Monte Carlo event
generators to simulate events which demand the evaluation of a matrix element. For
high multiplicity processes this can take up a significant portion of the time spent
simulating an event. In this thesis, we explore the usage of machine learning to accel-
erate the evaluation of matrix elements by introducing a factorisation-aware neural
network model. Matrix elements are plagued with singular structures in regions of
phase-space where particles become soft or collinear, however,...
quantities of experimental data to study the fundamental particles, and forces, of
nature. Theoretical predictions made with the SM can be compared with observables
measured at experiments. These predictions rely on the use of Monte Carlo event
generators to simulate events which demand the evaluation of a matrix element. For
high multiplicity processes this can take up a significant portion of the time spent
simulating an event. In this thesis, we explore the usage of machine learning to accel-
erate the evaluation of matrix elements by introducing a factorisation-aware neural
network model. Matrix elements are plagued with singular structures in regions of
phase-space where particles become soft or collinear, however,...
