A Very High Energy γ-Ray Survey toward the Cygnus Region of the Galaxy
Bibliographic record
Abstract
Abstract We present results from deep observations toward the Cygnus region using 300 hr of very high energy (VHE) γ -ray data taken with the VERITAS Cerenkov telescope array and over 7 yr of high-energy γ -ray data taken with the Fermi satellite at an energy above 1 GeV. As the brightest region of diffuse γ -ray emission in the northern sky, the Cygnus region provides a promising area to probe the origins of cosmic rays. We report the identification of a potential Fermi -LAT counterpart to VER J2031+415 (TeV J2032+4130) and resolve the extended VHE source VER J2019+368 into two source candidates (VER J2018+367* and VER J2020+368*) and characterize their energy spectra. The Fermi -LAT morphology of 3FGL J2021.0+4031e (the Gamma Cygni supernova remnant) was examined, and a region of enhanced emission coincident with VER J2019+407 was identified and jointly fit with the VERITAS data. By modeling 3FGL J2015.6+3709 as two sources, one located at the location of the pulsar wind nebula CTB 87 and one at the quasar QSO J2015+371, a continuous spectrum from 1 GeV to 10 TeV was extracted for VER J2016+371 (CTB 87). An additional 71 locations coincident with Fermi -LAT sources and other potential objects of interest were tested for VHE γ -ray emission, with no emission detected and upper limits on the differential flux placed at an average of 2.3% of the Crab Nebula flux. We interpret these observations in a multiwavelength context and present the most detailed γ -ray view of the region to date.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".