THE DISCOVERY OF γ-RAY EMISSION FROM THE BLAZAR RGB J0710+591
Bibliographic record
Abstract
The high-frequency-peaked BL Lacertae object RGB J0710+591 was observed in the very high-energy (VHE; E > 100 GeV) wave band by the VERITAS array of atmospheric Cherenkov telescopes. The observations, taken between 2008 December and 2009 March and totaling 22.1 hr, yield the discovery of VHE gamma rays from the source. RGB J0710+591 is detected at a statistical significance of 5.5 standard deviations (5.5σ) above the background, corresponding to an integral flux of (3.9 ± 0.8) × 10 −12 cm −2 s −1 (3% of the Crab Nebula's flux) above 300 GeV. The observed spectrum can be fit by a power law from 0.31 to 4.6 TeV with a photon spectral index of 2.69 ± 0.26 stat ± 0.20 sys . These data are complemented by contemporaneous multiwavelength data from the Fermi Large Area Telescope, the Swift X-ray Telescope, the Swift Ultra-Violet and Optical Telescope, and the Michigan–Dartmouth–MIT observatory. Modeling the broadband spectral energy distribution (SED) with an equilibrium synchrotron self-Compton model yields a good statistical fit to the data. The addition of an external-Compton component to the model does not improve the fit nor brings the system closer to equipartition. The combined Fermi and VERITAS data constrain the properties of the high-energy emission component of the source over 4 orders of magnitude and give measurements of the rising and falling sections of the SED.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".