Exploring New Frontiers in Particle Physics: Extended Higgs Sectors, Dark Matter, and Neutrino Masses
Bibliographic record
Abstract
This thesis explores four research projects in particle physics that aims in enhancing our understanding of the universe's fundamental particles and forces.The first part examines the Georgi-Machacek (GM) model, which expands the Standard Model (SM) scalar sector by including two SU (2) L triplets.We conduct a comprehensive analysis of the experimental status of this model.Our findings establish an experimental lower limit on the triplet vacuum expectation value that affects deviations from the SM in the Higgs boson's tree-level couplings.The second part explores breaking CP in a dark sector consisting of SM gauge singlets.We conduct a two-loop calculation in the effective theory, with the dark sector interacting with the SM sector via a vector Z portal and Higgs portal.Our findings demonstrate that collider constraints from B-factories exclude feasible baryogenesis for Z masses under 10 GeV.Additionally, future electron-positron Higgs factories may test the viable baryogenesis parameter space.I owe a huge debt of gratitude to all the amazing people who generously supported me throughout my graduate studies.Without their substantial contributions, this thesis wouldn't have been possible.To all those that helped me along my path, thank you.First of all, I must express my deepest thanks to my supervisors, Dr. Heather Logan and Dr. Daniel Stolarski.Their expertise and profound understanding of elementary particle physics have been invaluable, and I have gained tremendous knowledge and benefited greatly from their teachings.The numerous physics discussions and conversations were fundamental to my development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".