A new model and tests of the JEM-EUSO Balloon pathfinders Fresnel optics
Bibliographic record
Abstract
EUSO-Balloon and EUSO-SPB are balloon borne pathfinder projects designed to val- idate the techniques of the JEM-EUSO space observatory. They are nadir pointing UV telescopes that use experimental experimental Fresnel optics to detect the ultravi- olet emission of Extensive Air Showers (EAS) induced by Ultra High Energy Cosmic Rays (UHECR) in the atmosphere. EUSO-Balloon was launched by the balloon di- vision of CNES (the french space agency) from Timmins, Ontario, Canada in 2014. Despite the success of the mission the performance of the optics was lower than what it was originally modeled and led to many doubts regarding the understanding of the optics and fresnel lenses themselves. This thesis explores three parameters proposed to explain the reduction in eciency of the system which were not simulated in the original characterization: the rounded valleys in the Fresnel lens grooves created by the tool peak radii, scratches on the surface of the lenses and the surface roughness of the fresnel lenses. These parameters were simulated and results show that they show a reduction in performance which approximates more the characterization measure- ments but still do not match exactly, leaving room for further analysis. EUSO-SPB1 is the successor of EUSO-Balloon with a launch planned in 2017 from Wanaka, New Zealand. The results of the first phase of the optics characterization campaign is pre- sented in this work. The results indicate that the optics performance is similar to that of EUSO-Balloon and require further understanding.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".