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Record W4393316466 · doi:10.1002/asna.20240018

The <i>HST</i> Large Programme on NGC 6752 ‐ V. Differences in luminosity and mass function among stellar populations

2024· article· en· W4393316466 on OpenAlexfundno aff
M. Scalco, Roman Gerasimov, L. R. Bedin, Enrico Vesperini, D. Nardiello, M. Salaris, Adam J. Burgasser, Jay Anderson, Mattia Libralato, Andrea Bellini, P. Rosati

Bibliographic record

VenueAstronomische Nachrichten · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersMinistero dell'Istruzione e del MeritoScience and Technology Facilities CouncilNational Science FoundationInstitut sur la Nutrition et les Aliments FonctionnelsMinistero dell’Istruzione, dell’Università e della RicercaNational Aeronautics and Space AdministrationSpace Telescope Science Institute
KeywordsPhysicsAstrophysicsLuminosity functionAstronomyLuminosityStellar massGalaxyStar formation

Abstract

fetched live from OpenAlex

Abstract We exploit the astro‐photometric dataset of the multi‐epoch infrared parallel field of a Hubble Space Telescope Large Programme aimed at studying the faintest stars of the globular cluster NGC 6752 to determine the luminosity and mass functions of the multiple stellar populations of this cluster. Thanks to the measurement of proper motions and deeper completeness, the results presented in this paper represent a significant improvement over those of previous studies. We successfully derived membership probabilities reaching stars as faint as , allowing us to reliably distinguish the three main stellar populations detected within this cluster. We employed a new set of model isochrones that have been individually fit to the colour–magnitude diagram of each population. We present a comprehensive analysis of the luminosity and mass functions for three stellar populations within NGC 6752. Notably, our findings reveal differences in the present‐day luminosity and mass functions of first‐generation and second‐generation stars; these differences are consistent with the manifestation of the effects of dynamical processes acting on populations with different initial spatial distributions. Finally, we publicly release the catalogues with positions, photometry, proper motions and memberships probabilities, as well as the stacked‐image atlases and all newly calculated stellar models.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.228
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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