Exploring the Potential of the Pulsed Laser onboard the CALIPSO Satellite to Improve Calibration with VERITAS
Bibliographic record
Abstract
Imaging Atmospheric Cherenkov Telescopes (IACTs) are used to detect bright nanosecond-duration flashes of optical light originating from interactions of cosmic/gamma-rays in the atmosphere. A natural calibration source with similar characteristics does not exist; however, satellite-based laser systems provide a potential alternative. The CALIPSO satellite is one such facility which uses a suite of instruments to gather information about the atmosphere. Of particular interest is the CALIOP instrument, which emits 20-nanosecond laser pulses at 1064 nm and 532 nm at a rate of 20 Hz towards the Earth. The TAIGA-HiSCORE collaboration announced a detection of CALIOP laser pulses at the 37th ICRC in 2021, demonstrating that the laser footprint extends to at least tens of kilometers from the subsatellite point. We have used the VERITAS IACT to observe CALIPSO, and show here the results of using these observations to help to calibrate the array. We also discuss the potential of this technique for cross-calibration between different IACT facilities and for relative calibration between the telescopes of future large arrays.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".