THE WFC3 GALACTIC BULGE TREASURY PROGRAM: A FIRST LOOK AT RESOLVED STELLAR POPULATION TOOLS
Bibliographic record
Abstract
When the Wide Field Camera 3 (WFC3) is installed on the Hubble Space Telescope ( HST ), the astronomical community will have access to powerful new capabilities for investigating resolved stellar populations. The WFC3 Galactic Bulge Treasury program will obtain deep imaging in five photometric bands on four low-extinction fields. These data will have no proprietary period, and will enable a variety of science investigations not possible with previous data sets. To aid in planning for the use of these data and for future observing proposals, we provide an introduction to the Treasury program, its photometric system, and the associated calibration effort. The observing strategy is based upon a new photometric system employing five WFC3 bands spanning the UV, optical, and near-infrared: F390W, F555W, F814W, F110W, and F160W (analogous but not identical to the ground-based filters Washington C , V , I , J , and H ). With these bands, one can construct reddening-free indices of temperature and metallicity. Using this photometric system, the program will target six fields in well studied star clusters, spanning a wide range of metallicity, and four fields in low-extinction windows of the Galactic bulge. The cluster data serve to calibrate the reddening-free indices, provide empirical population templates, and correct the transformation of theoretical isochrone libraries into the WFC3 photometric system. The bulge data will shed light on the bulge formation history, and will also serve as empirical population templates for other studies. One of the fields includes 12 candidate hosts of extrasolar planets. Color–magnitude diagrams (CMDs) are the most popular tool for analyzing resolved stellar populations. However, due to degeneracies among temperature, metallicity, and reddening in traditional CMDs, it can be difficult to draw robust conclusions from the data. The five-band system used for the bulge Treasury observations will provide reddening-free indices that are roughly orthogonal in temperature and metallicity, and we argue that model fitting in an index–index diagram will make better use of the information than fitting separate CMDs. We provide some results from simulations to show the expected quality of the data and their potential for differentiating between different star formation histories.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".