Probes of new physics at the intensity and energy frontiers
Bibliographic record
Abstract
In this thesis, we review the basics of phenomenology in particle physics at neutrino beam dump experiments and hadron colliders. We then consider the phenomenology of various new particles, with masses between 1 MeV and 1 TeV, at the intensity and energy frontiers. We perform sensitivity analyses for physics beyond the standard model at particle colliders (LEP and LHC) and a number of past and future neutrino beam dump experiments (SHiP, DUNE, LSND, MicroBooNE, MiniBooNE and SBND). In particular, we motivate searches for new heavy neutral leptons in single photon events at neutrino and collider experiments (and also via supernova cooling), millicharged particles in single electron events at neutrino experiments, lepton flavor violating scalars via standard model induced mixed flavor neutrino trident production at neutrino experiments, and colored scalar doublets at colliders in events with many jets, soft leptons and low missing energy. In the process, we set novel new bounds on the parameters of these theories and propose powerful new searches that can be performed. We also motivate the construction of a new detector at the LHC called milliQan, and perform a full Geant4 simulation to calculate its projected sensitivity for millicharged particles. The milliQan experiment has since been approved and is currently undergoing construction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".