Physics of Eclipsing Binaries: Motivation for the New-Age Modeling Suite
Bibliographic record
Abstract
Recent ultra-high precision observations of eclipsing binaries, especially data acquired by the Kepler satellite, have made accurate light curve modelling increasingly challenging but also more rewarding. In this contribution, we discuss low-amplitude signals in light curves that can now be used to derive physical information about eclipsing binaries but that were unaccessible before the Kepler era. A notable example is the detection of Doppler beaming, which leads to an increase in flux when a star moves towards the satellite and a decrease in flux when it moves away. Similarly, Rpmer delays, or light travel time effects, also have to taken into account when modelling the supreme quality data that is now available. The detection of offsets between primary and secondary eclipse phases in binaries with extreme mass ratios, and the observation of Horner delays in the signals of pulsators in binary stars, have allowed us to determine the orbits of several binaries without the need for spectroscopy. A third example of a small-scale effect that has to be taken into account when modelling specific binary systems, are lensing effects. A new binary light curve modelling code, PHOEBE 2.0, that takes all these effect into account is currently being developed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".