A High-Contrast Imaging Survey of<i>SIM Lite</i>Planet Search Targets
Bibliographic record
Abstract
With the development of extreme high contrast ground-based adaptive optics instruments and space missions aimed at detecting and characterizing Jupiter- and terrestrial-mass planets, it is critical that each target star be thoroughly vetted to determine whether it is a viable target, given both the instrumental design and scientific goals of the program. With this in mind, we have conducted a high-contrast imaging survey of mature AFGKM stars with the PALAO/PHARO instrument on the Palomar 200 inch telescope. The survey reached sensitivities sufficient to detect brown dwarf companions at separations of >50 AU. The results of this survey will be utilized both by future direct imaging projects such as GPI, SPHERE, and P1640 and indirect detection missions such as SIM Lite . Out of 84 targets, all but one have no close-in (0.45–1'') companions and 64 (76%) have no stars at all within the 25'' field of view. The sensitivity contrasts in the K s passband ranged from 4.5 to 10 for this set of observations. These stars were selected as the best nearby targets for habitable planet searches because of their long-lived habitable zones (>1 billion years). We report two stars, GJ 454 and GJ 1020, with previously unpublished proper motion companions. In both cases, the companions are stellar in nature and are most likely M dwarfs based on their absolute magnitudes and colors. Based on our mass sensitivities and level of completeness, we can place an upper limit of ∼17% on the presence of brown dwarf companions with masses >40 M J at separations of >1''. We also discuss the importance of including statistics on those stars with no detected companions in their field of view for the sake of future companion searches and an overall understanding of the population of low-mass objects around nearby stars.
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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 | 0.001 |
| 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 | 0.000 | 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".