MASS TRANSFER IN BINARY STARS USING SMOOTHED PARTICLE HYDRODYNAMICS. I. NUMERICAL METHOD
Bibliographic record
Abstract
Close interactions and mass transfer in binary stars can lead to the formation of many different exotic stellar populations, but detailed modeling of mass transfer is a computationally challenging problem. Here, we present an alternate Smoothed Particle Hydrodynamics approach to the modeling of mass transfer in binary systems that allows a better resolution of the flow of matter between main-sequence stars. Our approach consists of modeling only the outermost layers of the stars using appropriate boundary conditions and ghost particles. We arbitrarily set the radius of the boundary and find that our boundary treatment behaves physically and conserves energy well. In particular, when used with our binary relaxation procedure, our treatment of boundary conditions is also shown to evolve circular binaries properly for many orbits. The results of our first simulation of mass transfer are also discussed and used to assess the strengths and limitations of our method. We conclude that it is well suited for the modeling of interacting binary stars. The method presented here represents a convenient alternative to previous hydrodynamical techniques aimed at modeling mass transfer in binary systems since it can be used to model both the donor and the accretor while maintaining the density profiles taken from realistic stellar models.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".