Fundamental physics with blazar spectra: a critical appraisal
Bibliographic record
Abstract
ABSTRACT Very-high-energy (VHE) BL Lacertae (BL Lac) spectra extending above $10 \, \rm TeV$ provide a unique opportunity for testing physics beyond the standard model of elementary particle and alternative blazar emission models. We consider the hadron beam scenario, the conversion of photons to axion-like particles (ALPs) and the Lorentz invariance violation (LIV) by analysing their consequences and induced modifications to BL Lac spectra. In particular, we consider how different processes can provide similar spectral features (e.g. hard tails) and we discuss the ways they can be disentangled. We use data from High-Energy Gamma-Ray Astronomy (HEGRA) of a high state of Markarian 501 and the High-Energy Stereoscopic System (H.E.S.S.) spectrum of the extreme BL Lac (EHBL) 1ES 0229+200. In addition, we consider two hypothetical EHBLs similar to 1ES 0229+200 located at redshifts z = 0.3 and z = 0.5. We observe that both the hadron beam and the photon–ALP oscillations predict a hard tail extending to energies larger than those possible in the standard scenario. Photon–ALP interaction predicts a peak in the spectra of distant BL Lacs at about $20\rm {-}30 \, \rm TeV$, while LIV produces a strong peak in all BL Lac spectra around $\sim 100 \, \rm TeV$. The peculiar feature of the photon–ALP conversion model is the production of oscillations in the spectral energy distribution, so that its detection/absence can be exploited to distinguish between the considered models. The above-mentioned features of the three models might be detected by the upcoming Cherenkov Telescope Array. Thus, future observations of BL Lac spectra could eventually shed light on new physics and alternative blazar emission models, driving fundamental research towards a specific direction.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| 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".