From Collisions to Predictions: Search for Non-Resonant Higgs Boson Pair Production in the Fully Leptonic bbWW Final State using CMS Run 3 Data

This thesis presents a comprehensive search for non-resonant Higgs boson pair production in the fully leptonic bbWW final state, utilizing data collected by the CMS experiment during Run 3 of the LHC. The research tracks a typical modern particle physics workflow from foundations to predictive analysis.

The journey begins with a deep dive into the theoretical framework of the Standard Model of particle physics, focusing on the mathematical formalism of the Brout-Englert-Higgs mechanism. To test these theories, the focus shifts to the experimental apparatus of the CMS detector at CERN—home to the world's most powerful superconducting electromagnet. This includes an exploration of the detector’s components, its commissioning, and the foundational methodologies required to process the massive amounts of collision data it produces.

The final stage of the research leverages cutting-edge machine learning algorithms, where mathematics and programming intersect to isolate rare physical phenomena from overwhelming background noise. By combining these advanced computational models with the experimental data and theoretical guidelines, the thesis demonstrates how a delicate search for rare signals is conducted at the CMS experiment, outlining the strategies used to tackle complex experimental challenges and extract meaningful predictions.