Characterizing the VHE emission of the extreme HBLs 1ES 1218+304 and 1ES 0229+200 with VERITAS
Bibliographic record
Abstract
The modelling of the spectral energy distribution (SED) of some high-frequency peaked BL Lac objects (HBLs) has proved challenging for the so-called extreme candidates, which can have their TeV peak at energies $>1$ TeV and a hard intrinsic TeV spectrum of $\Gamma<2$. The HBLs 1ES 1218+304 ($z=0.182$) and 1ES 0229+200 ($z=0.1396$) are two characteristic examples. Historically, leptonic one-zone synchrotron self-Compton (SSC) models have been used when modelling the broadband SED of BL Lac objects with relative success, but they fail to fully describe the emission of their extreme counterparts without requiring unexpectedly large or small physical quantities, or reaching far beyond the equipartition condition, when accounting for extragalactic background light (EBL). In this work, using archival VERITAS data from 2008 to 2021 on 1ES 1218+304 and 1ES 0229+200 combined with data from the Swift-XRT and Fermi-LAT observatories for extended wavelength coverage, we provide an updated look on the modelling of extreme HBLs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".