The Photometric Amplitude and Mass Ratio Distributions of Contact Binary Stars
Bibliographic record
Abstract
The distribution of the light-variation amplitudes, A(a), in addition to determining the number of undiscovered contact binary systems falling below photometric detection thresholds and thus lost to statistics, can serve as a tool in determination of the mass-ratio distribution, Q(q), which is very important for understanding of the evolution of contact binaries. Calculations of the expected A(a) show that it tends to converge to a mass-ratio dependent constant value for a->0. Strong dependence of A(a) on Q(q) can be used to determine the latter distribution, but the technique is limited by the presence of unresolved visual companions and by blending in crowded areas of the sky. The bright-star sample to 7.5 magnitude is too small for an application of the technique while the the Baade's Window sample from the OGLE project may suffer stronger blending; thus the present results are preliminary and illustrative only. Estimates based on the Baade's Window data from the OGLE project, for amplitudes a>0.3 mag. where the statistics appear to be complete allowing determination of Q(q) over 0.12<q<1, suggest a steep increase of Q(q) with q->0. The mass-ratio distribution can be approximated by a power law, either Q(q)~(1-q)^a1 with a1=6+/-2 or Q(q)~q^b1, with b1=-2+/-0.5, with a slight preference for the former form. Both forms must be modified by the theoretically expected cut-off caused by a tidal instability at about q_min 0.07-0.1. An expected maximum in Q(q), is expected to be mapped into a local maximum in A(a) around 0.2-0.25 mag.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".