Di-Higgs Production in the Standard Model and Beyond

Abstract: This thesis examines how the kinetic properties of pair-produced Higgs bosons depend on whether the process is mediated by particles in the Standard Model or a simplified supersymmetric model. The analysis is based on simulated data made using MadGraph. The examination within this thesis is split into two parts, one performed on the output of MadGraph (parton level) and the second performed on the output of a simplified simulation of the ATLAS detector response (reconstruction level). The first part also contains a section showing that the supersymmetric model results are consistent with the Standard Model results in cases where no supersymmetric particles are present in the di-Higgs production and decay, and a section detailing the minor differences in kinematics of the Higgs bosons depending on the mass of the supersymmetric partner of the top quark. The second part of the thesis covers the decay of the Higgs boson into bottom and anti-bottom quarks, and includes a section showing that there is no difference if the decay is done using the MadSpin module or the Pythia module for MadGraph, before exploring the kinematics of the jets produced. Both when studying Higgs bosons at the parton level and when studying b-jets at the reconstruction level, it is found that there are clear differences in the kinematics between the Standard Model and the supersymmetric model. At both levels, a neural network has been designed, trained and tested. For the parton level neural network 59 % of all events are classified correctly, while at the reconstruction level 51 % of all events are classified correctly. These neural network results show that it is possible to train a neural network to learn on data like this, and that with enough di-Higgs events detected, their kinematic properties could be used to indirectly infer the presence of physics beyond the Standard Model.