New jet feature in the parsec-scale jet of the blazar OJ 287 connected to the 2017 teraelectronvolt flaring activity
Bibliographic record
Abstract
Context.In February 2017 the blazar OJ 287, one of the best super-massive binary-black-hole-system candidates, was detected for the first time at very high energies (VHEs;E > 100 GeV) with the ground-basedγ-ray observatory VERITAS. Aims.Very high energyγrays are thought to be produced in the near vicinity of the central engine in active galactic nuclei. For this reason, and with the main goal of providing useful information for the characterization of the physical mechanisms connected with the observed teraelectronvolt flaring event, we investigate the parsec-scale source properties by means of high-resolution very long baseline interferometry observations. Methods.We use 86 GHz Global Millimeter-VLBI Array (GMVA) observations from 2015 to 2017 and combine them with additional multiwavelength radio observations at different frequencies from other monitoring programs. We investigate the source structure by modeling the brightness distribution with two-dimensional Gaussian components in the visibility plane. Results.In the GMVA epoch following the source VHE activity, we find a new jet feature (labeled K) at ∼0.2 mas from the core region and located in between two quasi-stationary components (labeled S1 and S2). Multiple periods of enhanced activity are detected at different radio frequencies before and during the VHE flaring state. Conclusions.Based on the findings of this work, we identify as a possible trigger for the VHE flaring emission during the early months of 2017 the passage of a new jet feature through a recollimation shock (represented by the model-fit component S1) in a region of the jet located at a de-projected distance of ∼10 pc from the radio core.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".