General relativistic dynamical tides in binary inspirals without modes
Bibliographic record
Abstract
A neutron star in an inspiraling binary system is tidally deformed by its companion, and the effect leaves a measurable imprint on the emitted gravitational waves. While the tidal interaction falls within the regime of static tides during the early stages of inspiral, a regime of dynamical tides takes over in the later stages. The description of dynamical tides found in the literature makes integral use of a spectral representation of the tidal deformation, in which it is expressed as a sum over the star's normal modes of vibration. This description is deeply rooted in Newtonian fluid mechanics and gravitation, and we point out that considerable obstacles manifest themselves in an extension to general relativity. To remedy this, we propose an alternative, modeless description of dynamical tides that can be formulated in both Newtonian and relativistic mechanics. Our description is based on a time-derivative expansion of the tidal dynamics, in which the external, orbital timescale associated with the tidal field is taken to be long compared with the internal, hydrodynamical timescale associated with the neutron star. The tidal deformation is characterized by two sets of Love numbers: the familiar static Love numbers ${k}_{\ensuremath{\ell}}$, which appear in the regime of static tides, and the dynamic Love numbers ${\stackrel{\ifmmode\ddot\else\textasciidieresis\fi{}}{k}}_{\ensuremath{\ell}}$, which emerge in the regime of dynamical tides. These numbers are computed here for polytropic stellar models in both Newtonian gravity and general relativity. On the face of it, the time-derivative expansion of the tidal dynamics seems to preclude any attempt to capture an approach to resonance, which occurs when the frequency of the tidal field becomes equal to a normal-mode frequency; such an approach is the main reason for which the regime of dynamical tides becomes important in the late inspiral, and it is fully captured by the mode representation of the tidal deformation. To overcome this limitation, we propose a pragmatic extension of the time-derivative expansion, which does capture an approach to resonance. We demonstrate that with this extension, our formulation of dynamical tides should be just as accurate as the $f$-mode truncation of the mode representation, in which the sum over modes is truncated to a single term involving the star's fundamental mode of vibration.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".