JWST uncovers helium and water abundance variations in the bulge globular cluster NGC 6440
Bibliographic record
Abstract
We used ultra-deep observations obtained with the NIRCam aboard the James Webb Space Telescope to explore the stellar population of NGC 6440: a typical massive, obscured, and contaminated globular cluster formed and orbiting within the Galactic bulge. Leveraging the exceptional capabilities of this camera, we sampled the cluster down to about five magnitudes below the main sequence turn-off in the ( m F 115 W , m F 115 W − m F 200 W ) colour–magnitude diagram. After carefully accounting for differential extinction and contamination by field interlopers, we find that the main sequence splits into two branches, each above and below the characteristic knee. By comparing the morphology of the colour–magnitude diagram with a suitable set of isochrones, we argue that the upper main sequence bi-modality is likely due to the presence of a He-enriched stellar population with a helium spread of Δ Y = 0.04. The lower main sequence bi-modality can be attributed to variations in the abundance of water (i.e., oxygen) with Δ[O/Fe] ∼ −0.4. This is the first evidence of both helium and oxygen abundance variations in a globular cluster purely based on JWST observations. These results open the window for future in-depth investigations of the multiple population phenomenon in clusters located in the Galactic bulge, which were previously unfeasible with near-UV observations, due to prohibitive reddening and crowding conditions.
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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 | 0.001 |
| 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".