TOWARD PRECISION PHOTOMETRY FOR THE ELT ERA: THE DOUBLE SUBGIANT BRANCH OF NGC 1851 OBSERVED WITH THE GEMINI/GeMS MCAO SYSTEM
Bibliographic record
Abstract
The Extremely Large Telescopes currently under construction have a collecting area that is an order of magnitude larger than the present largest optical telescopes. For seeing-limited observations the performance will scale as the collecting area, but with the successful use of adaptive optics (AO), for many applications it will scale as D 4 (where D is the diameter of the primary mirror). Central to the success of the ELTs, therefore, is the successful use of multi-conjugate adaptive optics (MCAO) which applies a high degree of correction over a field of view larger than the few arcseconds that limits classical AO systems. In this Letter, we report on the analysis of crowded field images taken on the central region of the galactic globular cluster NGC 1851 in the K s band using the Gemini Multi-conjugate Adaptive Optics System (GeMS) at the Gemini South Telescope, the only science-grade MCAO system in operation. We use this cluster as a benchmark to verify the ability to achieve precise near-infrared photometry by presenting the deepest K s photometry in crowded fields ever obtained from the ground. We construct a color–magnitude diagram in combination with the F606W band from the Hubble Space Telescope /Advanced Camera for Surveys. As well as detecting the "knee" in the lower main sequence at K s ≃ 20.5, we also detect the double subgiant branch of NGC 1851, which demonstrates the high photometric accuracy of GeMS in crowded fields.
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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 | 0.001 | 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 | 0.001 | 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".