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Record W4317852590 · doi:10.1051/0004-6361/202244906

Quantitative spectroscopy of late O-type main-sequence stars with a hybrid non-LTE method

2023· article· en· W4317852590 on OpenAlexfundno aff
P. Aschenbrenner, N. Przybilla, K. Butler

Bibliographic record

VenueAstronomy and Astrophysics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersMasarykova UniverzitaEuropean Space AgencyCalifornia Institute of TechnologyNational Aeronautics and Space AdministrationCanadian Space AgencyJet Propulsion LaboratorySpace Telescope Science InstituteUniversity of California, Los AngelesInstituto de Astrofísica de AndalucíaNational Science Foundation
KeywordsPhysicsAstrophysicsStarsHydrostatic equilibriumSpectral lineStellar atmosphereSupergiantLuminosityLine (geometry)Effective temperatureAtmospheric modelGalaxyAstronomy

Abstract

fetched live from OpenAlex

Context. Late O-type stars at luminosities log L / L ⊙ ≲ 5.2 show weak winds with mass-loss rates lower than 10 −8 M ⊙ yr −1 . This implies that, unlike their more massive and more luminous siblings, their photospheric layers are not strongly affected by the stellar wind. Aims. A hybrid non-local thermodynamic equilibrium (non-LTE) approach – line-blanketed hydrostatic model atmospheres computed under the assumption of LTE in combination with non-LTE line-formation calculations – is tested for analyses of late O-type stars with masses up to ~25 M ⊙ . A sample of 20 mostly sharp-lined Galactic O stars of spectral types O8 to O9.7 and luminosity classes V and IV, previously studied in the literature using full non-LTE model atmospheres, is investigated. Methods. Hydrostatic and plane-parallel atmospheric structures and synthetic spectra computed with Kurucz’s A TLAS 12 code together with the non-LTE line-formation codes D ETAIL and S URFACE , which account for the effects of turbulent pressure on the atmosphere, were employed. High-resolution spectra were analysed for atmospheric parameters using hydrogen lines, multiple ionisation equilibria, and elemental abundances. Fundamental stellar parameters were derived by considering stellar evolution tracks and Gaia Early Data Release 3 (EDR3) parallaxes. Interstellar reddening was characterised by fitting spectral energy distributions from the UV to the mid-IR. Results. A high precision and accuracy is achieved for all derived parameters for 16 sample stars (4 objects show composite spectra). Turbulent pressure effects turn out to be significant for the quantitative analysis. Effective temperatures are determined to 1–3% uncertainty levels, surface gravities to 0.05 to 0.10 dex, masses to better than 8%, radii to better than 10%, and luminosities to better than 20% uncertainty typically. Abundances for C, N, O, Ne, Mg, Al, and Si are derived with uncertainties of 0.05–0.10 dex and for helium within 0.03–0.05 dex (1 σ standard deviations) in general. Overall, results from previous studies using unified photosphere plus wind (full) non-LTE model atmospheres are reproduced, and with higher precision. The improvements are most pronounced for elemental abundances, and smaller microturbulent velocities are found. An overall good agreement is found between our spectroscopic distances and those from Gaia. Gaia EDR3-based distances to the Lac OB1b association and to the open clusters NGC 2244, IC 1805, NGC 457, and IC 1396 are determined as a byproduct. The derived N/C versus N/O abundance ratios tightly follow the predictions from stellar evolution models. Two ON stars show a very high degree of mixing of CNO-processed material and appear to stem from binary evolution.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.271
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2023
Admission routes1
Has abstractyes

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