Commissioning of the ATLAS Electron and Photon Trigger Selection
Bibliographic record
Abstract
Since the start-up of the LHC end of 2009, the trigger commissioning is in full swing. The ATLAS trigger system is divided into three levels: the hardware-based first level trigger, and the software-based second level trigger and Event Filter, collectively referred to as the High Level Trigger (HLT). Initially, events have been selected online based on the Level-1 selections with the HLT algorithms run but not rejecting any events. This has been an important step in the commissioning of these triggers to ensure their correct functioning and subsequently to enable the HLT selections. Due to increasing LHC luminosity and the large QCD cross section, this has been a vital step to select leptons from J/Psi, bottom, charm, W and Z decays. This presentation gives an overview of the trigger performance of the electron and photon selection. Comparisons of the online selection variables with the offline reconstruction are shown as well as comparisons of data with MC simulations on which the current selection tuning is performed. Finally, an outlook will be given on the strategy how the electron and photon menus will evolve with increasing luminosities.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.010 |
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".