Revisiting the evidences for spectral anomalies in distant blazars: New data on the photon-ALP mixing
Bibliographic record
Abstract
ABSTRACT We re-examine possible dependencies on redshift of the spectral parameters of blazars observed at very-high energies (VHEs) with Imaging Atmospheric Cherenkov telescopes. This is relevant to assess potential effects with the source distance of the photon to axion-like particle mixing that would deeply affect the propagation of VHE photons across the Universe. We focus our spectral analysis on 38 BL Lac objects (32 high-peaked and 6 intermediate-peaked) up to redshift z ≃ 0.5, and a small sample of 5 Flat Spectrum Radio Quasars up to z = 1 treated independently to increase the redshift baseline. The 78 independent spectra of these sources are first of all carefully corrected for the gamma–gamma interaction with photons of the Extragalactic Background Light that are responsible for the major redshift-dependent opacity effect. Then, the corrected spectra are fitted with simple power laws to infer the intrinsic spectral indices Γem at VHE, to test the assumption that such spectral properties are set by the local rather than the global cosmological environment. We find some systematic anticorrelations with redshift of Γem that might indicate, although with low-significance, a spectral anomaly potentially requiring a revision of the photon propagation process. More conclusive tests with higher statistical significance will require the observational improvements offered by the forthcoming new generation of Cherenkov arrays (CTA, ASTRI, LHAASO).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".