First Lorentz Invariance Violation constraint from a cooperation of Imaging Atmospheric Cherenkov Telescopes
Bibliographic record
Abstract
Lorentz invariance violation (LIV) may arise from modifications to the dispersion relation of massless particles in effective models attempting to merge quantum field theories and general relativity. One way to detect or constrain LIV effects is by measuring time delays in the arrival of high-energy photons from astrophysical sources. Suitable targets are variable, distant and highly energetic objects such as pulsars, gamma-ray bursts (GRBs), and active galactic nuclei (AGN) flares. However, a major challenge arises from intrinsic time lags due to source-specific emission processes. To improve the precision of these measurements and distinguish potential LIV-induced delays from intrinsic effects, as well as improve the current exploration of LIV up to a higher energy scale, a collaborative effort has been established among major Imaging Atmospheric Cherenkov Telescopes (IACTs): H.E.S.S., MAGIC, VERITAS, and the first Large-Sized Telescope (LST-1) of CTAO. The so-called Gamma-ray LIV Working Group aims to combine observational data from multiple sources, enhancing the sensitivity and robustness of LIV searches. We present the first set of limits on the LIV energy scale derived from a combination of real data from IACTs experiments.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".