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Record W2750870267 · doi:10.1051/epjconf/201715205005

Determining the core stratification in white dwarfs with asteroseismology

2017· article· en· W2750870267 on OpenAlexafffund
S. Charpinet, N. Giammichele, P. Brassard, G. Fontaine

Bibliographic record

VenueEPJ Web of Conferences · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
FundersCentre National de la Recherche ScientifiqueFonds Québécois de la Recherche sur la Nature et les TechnologiesCentre National d’Etudes Spatiales
KeywordsAsteroseismologyStratification (seeds)White dwarfStarsDegenerate energy levelsAstrophysicsPhysicsCore (optical fiber)Optics

Abstract

fetched live from OpenAlex

Using the forward modeling approach and a new parameterization for the core chemical stratification in ZZ Ceti stars, we test several situations typical of the usually limited constraints available, such as small numbers of observed independent modes, to carry out asteroseismology of these stars. We find that, even with a limited number of modes, the core chemical stratification (in particular, the location of the steep chemical transitions expected in the oxygen profile) can be determined quite precisely due to the significant sensitivity of some confined modes to partial reflexion (trapping) effects. These effects are similar to the well known trapping induced by the shallower chemical transitions at the edge of the core and at the bottom of the H-rich envelope. We also find that success to unravel the core structure depends on the information content of the available seismic data. In some cases, it may not be possible to isolate a unique, well-defined seismic solution and the problem remains degenerate. Our results establish that constraining the core chemical stratification in white dwarf stars based solely on asteroseismology is possible, an opportunity that we have started to exploit.

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 score0.198
Threshold uncertainty score0.203

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 head0.042
GPT teacher head0.272
Teacher spread0.230 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

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