A Wolf 359 in Sheep's Clothing: Hunting for Substellar Companions in the Fifth-closest System Using Combined High-contrast Imaging and Radial Velocity Analysis
Bibliographic record
Abstract
Abstract Wolf 359 (CN Leo, GJ 406, Gaia DR3 3864972938605115520) is a low-mass star in the fifth-closest neighboring system (2.41 pc). Because of its relative youth and proximity, Wolf 359 offers a unique opportunity to study substellar companions around M stars using infrared high-contrast imaging and radial velocity monitoring. We present the results of Ms-band (4.67 μm) vector vortex coronagraphic imaging using Keck-NIRC2 and add 12 Keck-HIRES and 68 MAROON-X velocities to the radial velocity baseline. Our analysis incorporates these data alongside literature radial velocities from CARMENES, the High Accuracy Radial velocity Planet Searcher, and Keck-HIRES to rule out the existence of a close (a < 10 au) stellar or brown dwarf companion and the majority of large gas giant companions. Our survey does not refute or confirm the long-period radial velocity candidate, Wolf 359 b (P ∼ 2900 days), but rules out the candidate's existence as a large gas giant (>4 M Jup) assuming an age of younger than 1 Gyr. We discuss the performance of our high-contrast imaging survey to aid future observers using Keck-NIRC2 in conjunction with the vortex coronagraph in the Ms band and conclude by exploring the direct imaging capabilities with JWST to observe Jupiter- and Neptune-mass planets around Wolf 359.
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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 | 0.001 | 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".