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Active red giants: Close binaries versus single rapid rotators

2020· article· en· W6903211066 on OpenAlexfundno aff

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratorySmithsonian Astrophysical ObservatoryUniversity of Colorado BoulderOffice of ScienceMax-Planck-Institut für AstronomieMinistério da Ciência, Tecnologia e InovaçãoFundação para a Ciência e a TecnologiaCentre National d’Etudes SpatialesUniversity of OxfordYork UniversityLeibniz-GemeinschaftUniversity of Notre DameInstituto de Astrofísica de CanariasCarnegie Mellon UniversityYale UniversityDeutsches Zentrum für Luft- und RaumfahrtAlfred P. Sloan FoundationUniversity of WashingtonJohns Hopkins UniversityCarnegie Institution of WashingtonUniversity of UtahOhio State UniversityU.S. Department of EnergySmithsonian InstitutionNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityMax-Planck-Institut für Astrophysik
KeywordsStarsRed giantRed clumpAsteroseismologyAmplitudeOscillation (cell signaling)Binary star

Abstract

fetched live from OpenAlex

Oscillating red-giant stars have provided a wealth of asteroseismic information regarding their interiors and evolutionary states, which enables detailed studies of the Milky Way. The objective of this work is to determine what fraction of red-giant stars shows photometric rotational modulation, and understand its origin. One of the underlying questions is the role of close binarity in this population, which relies on the fact that red giants in short-period binary systems (less than 150 days or so) have been observed to display strong rotational modulation. We selected a sample of about 4500 relatively bright red giants observed by Kepler, and show that about 370 of them (∼8%) display rotational modulation. Almost all have oscillation amplitudes below the median of the sample, while 30 of them are not oscillating at all. Of the 85 of these red giants with rotational modulation chosen for follow-up radial-velocity observation and analysis, 34 show clear evidence of spectroscopic binarity. Surprisingly, 26 of the 30 nonoscillators are in this group of binaries. On the contrary, about 85% of the active red giants with detectable oscillations are not part of close binaries. With the help of the stellar masses and evolutionary states computed from the oscillation properties, we shed light on the origin of their activity. It appears that low-mass red-giant branch stars tend to be magnetically inactive, while intermediate-mass ones tend to be highly active. The opposite trends are true for helium-core burning (red clump) stars, whereby the lower-mass clump stars are comparatively more active and the higher-mass ones are less active. In other words, we find that low-mass red-giant branch stars gain angular momentum as they evolve to clump stars, while higher-mass ones lose angular momentum. The trend observed with low-mass stars leads to possible scenarios of planet engulfment or other merging events during the shell-burning phase. Regarding intermediate-mass stars, the rotation periods that we measured are long with respect to theoretical expectations reported in the literature, which reinforces the existence of an unidentified sink of angular momentum after the main sequence. This article establishes strong links between rotational modulation, tidal interactions, (surface) magnetic fields, and oscillation suppression. There is a wealth of physics to be studied in these targets that is not available in the Sun.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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