Thermal Infrared Imaging of MWC 758 with the Large Binocular Telescope: Planetary-driven Spiral Arms?
Bibliographic record
Abstract
Abstract Theoretical studies suggest that a giant planet around the young star MWC 758 could be responsible for driving the spiral features in its circumstellar disk. Here, we present a deep imaging campaign with the Large Binocular Telescope with the primary goal of imaging the predicted planet. We present images of the disk in two epochs in the L′ filter (3.8 μm) and a third epoch in the M′ filter (4.8 μm). The two prominent spiral arms are detected in each observation, which constitute the first images of the disk at M′, and the deepest yet in L′ (ΔL′ = 12.1 exterior to the disk at 5σ significance). We report the detection of an S/N ∼ 3.9 source near the end of the Southern arm, and, from the source’s detection at a consistent position and brightness during multiple epochs, we establish a ∼90% confidence-level that the source is of astrophysical origin. We discuss the possibilities that this feature may be (a) an unresolved disk feature, and (b) a giant planet responsible for the spiral arms, with several arguments pointing in favor of the latter scenario. We present additional detection limits on companions exterior to the spiral arms, which suggest that a ≲4 M Jup planet exterior to the spiral arms could have escaped detection. Finally, we do not detect the companion candidate interior to the spiral arms reported recently by Reggiani et al., although forward modeling suggests that such a source would have likely been detected.
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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) | 0.002 | 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".