Tidal Synchronization Trapping in Stars and Planets with Convective Envelopes
Bibliographic record
Abstract
Abstract Tidal torques can alter the spins of tidally interacting stars and planets, usually over shorter timescales than the tidal damping of orbital separations or eccentricities. Simple tidal models predict that, in eccentric binary or planetary systems, rotation periods will evolve toward a “pseudosynchronous” ratio with the orbital period. However, this prediction does not account for “inertial” waves that are present in stars or gaseous planets with (i) convective envelopes and (ii) even very slow rotation. We demonstrate that tidal driving of inertial oscillations in eccentric systems generically produces a network of stable “synchronization traps” at ratios of orbital to rotation period that are simple to predict but can deviate significantly from pseudosynchronization. The mechanism underlying spin synchronization trapping is similar to tidal resonance locking, involving a balance between torques that is maintained automatically by the scaling of inertial mode frequencies with the rotation rate. In contrast with many resonance locking scenarios, however, the torque balance required for synchronization trapping need not drive mode amplitudes to nonlinearity. Synchronization traps may provide an explanation for low-mass stars and hot Jupiters with observed rotation rates that deviate from pseudosynchronous or synchronous expectations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".