Effectively cornering new physics at colliders and beyond

Abstract

The Standard Model has achieved remarkable success, yet growing empirical and theoretical tensions point to the need for new physics at the TeV scale. As collider experiments enter a precision era, even small deviations from Standard Model predictions can provide crucial clues about the underlying structure of fundamental interactions. This thesis explores these possibilities through both model-dependent studies and the effective field theory approach. Multi-Higgs production is used to probe extended scalar sectors, offering insight into the nature of electroweak symmetry breaking and the dynamics of possible phase transitions. Electroweak-scale triplet models are examined through collider signatures and flavour constraints, presenting a realistic mechanism for radiative neutrino mass generation. In the top-quark sector, momentum-dependent width effects are implemented in a gauge-consistent way, leading to more accurate predictions for SMEFT constraints. To address the challenge of high-multiplicity final states, machine learning techniques, including graph neural networks, are applied to identify hidden correlations and enhance signal sensitivity. Together, these studies sharpen existing bounds and provide complementary strategies to guide future experimental efforts at the High-Luminosity LHC and beyond