Using Electrons and Photons to Estimate Passive Material Before the ATLAS Electromagnetic Calorimeter
Bibliographic record
Abstract
The ATLAS detector is a large, general-purpose particle detector designed to observe high-energy particle collisions on the Large Hadron Collider at CERN.This study uses electrons and photons from Run 2 proton-proton collision data (2015 -2016) to check for differences between real and simulated detector material in the region before the first layer of the electromagnetic (EM) calorimeter.The main probe is the ratio of energies deposited in the first and second layers of the EM calorimeter.The measured material differences are compared against results from similar studies performed using Run 1 data.Deviations between Run 1 and Run 2 results are observed, primarily in regions where detector hardware was upgraded before Run 2. The material differences are well accounted for by combining the existing Run 1 material systematic uncertainties with additional Run 2 uncertainties related to the new inner tracking layer (the IBL) and the modified PP0 service region. Statement of OriginalityTo give context to the author's work, this thesis contains several chapters dedicated to providing an overview of the scientific field ( experimental high-energy physics) and specific experimental conditions in which the research was conducted.Chapters 1 -3 and Sections A.1 -A.3 in the Appendix use material from several published sources to summarize the necessary scientific background.The author's original research is documented in Chapter 4.Where tables and figures are not created by the author, it is explicitly noted.The author spent several extended periods on-site at CERN in Geneva, working in close collaboration with the ATLAS electron and photon performance group.Early results were presented to the performance group at-large at a November 2016 workshop in Thessaloniki.Regular updates were delivered in the form of short oral presentations (either in person, or when not local to CERN, over video conferencing software) to the electron and photon calibration subgroup.Results from this thesis were used to provide electron and photon calibration recommendations for physics analyses presenting results at summer 2017 conferences.Figure 37 appeared on the ATLAS electron and photon calibration poster shown at the 2017 EPS conference [1].An ATLAS publication on the Run 2 calibration effort, which will include results from this work, is currently in production.Sections of Chapter 4 of this thesis have been assembled by the author into an ATLAS internal support note for the upcoming paper.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".