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Record W3101144423

Pulsation analysis of V 588 MON AND V 589 MON observed with the MOST AND CoRoT satellites

2013· article· en· W3101144423 on OpenAlexaff
K. Zwintz, T. Kallinger, D. B. Guenther, M. Gruberbauer, R. Kuschnig, W. W. Weiß, M. Auvergne, L. Jordá, F. Favata, J. M. Matthews, Markus Fischer

Bibliographic record

VenueSaint Mary's University Institutional Repository (Saint Mary's University) · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsSaint Mary's UniversitySt. Mary's UniversityUniversity of British Columbia
Fundersnot available
KeywordsPhysicsAstrophysicsAmplitudeStarsOscillation (cell signaling)Spectral lineNoise (video)Superposition principleRotation (mathematics)AstronomyOpticsGeometry
DOInot available

Abstract

fetched live from OpenAlex

The two pulsating pre-main sequence (PMS) stars V 588 Mon and V 589 Mon were observed by CoRoT for 23.4 days in March 2008 during the Short Run SRa01 and in 2004 and 2006 by MOST for a total of ~70 days. We present their photometric variability up to 1000 $\mu$ Hz and down to residual amplitude noise levels of 23 and 10 ppm of the CoRoT data for V 588 Mon and V 589 Mon, respectively. The CoRoT imagette data as well as the two MOST data sets allowed for detailed frequency analyses using Period04 and SigSpec. We confirm all previously identified frequencies, improve the known pulsation spectra to a total of 21 frequencies for V 588 Mon and 37 for V 589 Mon and compare them to our PMS model predictions. No model oscillation spectrum with l = 0, 1, 2, and 3 p-modes matches all the observed frequencies. When rotation is included we find that the rotationally split modes of the slower rotating star, V 589 Mon, are addressable via perturbative methods while for the more rapidly rotating star, V 588 Mon, they are not and, consequently, will require more sophisticated modeling. The high precision of the CoRoT data allowed us to investigate the large density of frequencies found in the region from 0 to 300 $\mu$Hz. The presence of granulation appears to be a more attractive explanation than the excitation of high-degree modes. Granulation was modeled with a superposition of white noise, a sum of Lorentzian-like functions and a Gaussian. Our analysis clearly illustrates the need for a more sophisticated granulation model.

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 score0.059
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.009
GPT teacher head0.164
Teacher spread0.156 · 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

Citations14
Published2013
Admission routes1
Has abstractyes

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