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Record W3126329602 · doi:10.3847/1538-3881/abf097

Tidal Circularization of Binaries by Resonance Locking. I. The Importance of the Pre-main Sequence

2021· article· en· W3126329602 on OpenAlexaff

Bibliographic record

VenueThe Astronomical Journal · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of TorontoCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsResonance (particle physics)Binary numberDissipationBinary starOrbital decayOscillation (cell signaling)HarmonicsTidal accelerationStars

Abstract

fetched live from OpenAlex

Abstract Although tidal dissipation in binary stars has been studied for over a century, theoretical predictions have yet to match the observed properties of binary populations. This work quantitatively examines the recent proposal of tidal circularization by resonance locking, where tidal dissipation arises from resonances between the star’s natural oscillation frequencies and harmonics of the orbital frequency, and where resonances are “locked” for an extended period of time due to concurrent stellar evolution. We focus on tidal resonances with axi-symmetric gravity modes, and examine binaries with primary masses from one to two solar masses. We find that orbital evolution via resonance locking occurs primarily during the star’s pre-main-sequence phase, with the main-sequence phase contributing negligibly. Resonance locking, ignoring nonlinearity, can circularize binaries with peri-center distances out to ∼10 stellar radii, corresponding to circular periods of ∼4–6 days. However, we find resonantly excited gravity modes will become nonlinear in stellar cores, which prevents them from reaching their full, linear amplitudes. We estimate that such a “saturated resonance lock” reduces the circularization period by about a third, but resonance locking remains much more effective than the cumulative actions of equilibrium tides. In a companion paper, we examine recent binary data to compare against theory.

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 score0.007
Threshold uncertainty score0.220

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 head0.011
GPT teacher head0.224
Teacher spread0.214 · 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

Citations38
Published2021
Admission routes1
Has abstractyes

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