Bibliographic record
Abstract
This thesis involves phenomenological models for describing high energy particle collisions. One class of these models, multiparton interactions (MPI), deals with the fact that when colliding two hadrons, it is possible for more than one pair of their constituents to interact. The other deals with parton showers, which are used to fill enhanced regions of phase space and give fully exclusive final states. These two components, when part of an event generation framework, help in the simulation of complete high energy collision events. Paper I presents a study of an extension to the MPI model, enhanced screening, where the amount of colour screening in an incoming hadron is increased in those events with a large amount of activity. Paper II presents another extension to the MPI model, rescattering. Commonly, in MPI models, interactions are between pairs of partons which originate from the incoming hadrons. With rescattering, an MPI can instead involve partons which come from previous interactions or shower branchings. Paper III studies the first emission of the parton shower. First, the interface to a next-to-leading generator, POWHEG-hvq, is examined. Second, a dampening of the first shower emission, based on general matrix element arguments is studied. Paper IV again deals with parton showers. Minor changes to the framework are outlined, before a kinematic comparison of the shower is made against 2 to 3 QCD real emission matrix elements. Finally, tunes of the generator are made to both Tevatron and LHC data. Paper V examines an extension to the impact parameter formalism of the MPI model, where the size of an incoming proton is varied depending on the x value of a parton being taken from it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".