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Record W4378388225 · doi:10.1093/mnras/stad1574

Carbon dredge-up required to explain the <i>Gaia</i> white dwarf colour–magnitude bifurcation

2023· article· en· W4378388225 on OpenAlexafffund
Simon Blouin, Antoine Bédard, Pier-Emmanuel Tremblay

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of Victoria
FundersH2020 European Research CouncilNatural Sciences and Engineering Research Council of CanadaEuropean CommissionKavli Institute for Theoretical Physics, University of California, Santa BarbaraNational Science Foundation
KeywordsWhite dwarfPhysicsAstrophysicsHeliumHydrogenCarbon starBifurcationAtmosphere (unit)Accretion (finance)StarsAtomic physicsThermodynamics

Abstract

fetched live from OpenAlex

ABSTRACT The Gaia colour–magnitude diagram reveals a striking separation between hydrogen-atmosphere white dwarfs and their helium-atmosphere counterparts throughout a significant portion of the white dwarf cooling track. However, pure-helium atmospheres have Gaia magnitudes that are too close to the pure-hydrogen case to explain this bifurcation. To reproduce the observed split in the cooling sequence, it has been shown that trace amounts of hydrogen and/or metals must be present in the helium-dominated atmospheres of hydrogen-deficient white dwarfs. Yet, a complete explanation of the Gaia bifurcation that takes into account known constraints on the spectral evolution of white dwarfs has thus far not been proposed. In this work, we attempt to provide such a holistic explanation by performing population synthesis simulations coupled with state-of-the-art model atmospheres and evolutionary calculations that account for element transport in the envelopes of white dwarfs. By relying on empirically grounded assumptions, these simulations successfully reproduce the bifurcation. We show that the convective dredge-up of optically undetectable traces of carbon from the deep interior is crucial to account for the observations. Neither the convective dilution/mixing of residual hydrogen nor the accretion of hydrogen or metals can be the dominant drivers of the bifurcation. Finally, we emphasize the importance of improving theoretical models for the average ionization level of carbon in warm dense helium, which governs the shape of the diffusive tail of carbon and in turn the predicted amount of dredged-up carbon.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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 designSimulation or modeling
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

Citations24
Published2023
Admission routes2
Has abstractyes

Explore more

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