On the treatment of entropy mixing in numerical cosmology
Bibliographic record
Abstract
For simulations of fluid dynamics in astrophysics, physical viscosity and diffusion are typically neglected. However, in this high Reynolds number regime, real fluids become highly turbulent and turbulent processes mediate substantial transport of momentum and heat that is diffusive in nature. In the absence of models for these processes, code-dependent numerical effects dominate how diffusion operates and may lead to physically incorrect simulation results. We highlight the qualitative difference in these numerical effects for smooth particle hydrodynamics (SPH) and grid-based Eulerian codes using two test problems: a buoyant gas bubble and gas in a galaxy cluster. Grid codes suffer from numerical diffusion in the absence of explicit terms, and small-scale diffusion of heat is completely absent in the Lagrangian SPH method. We find that SPH with heat diffusion added at a level similar to that expected from turbulence diffusion generates more physically appealing results. These results suggest, but do not confirm, that a flat entropy core is to be expected for gas in an idealized galaxy cluster (i.e. one without physics beyond that of a non-radiating gas). A goal of this work is thus to draw attention to the as yet unfulfilled need for models of turbulent diffusive processes in compressible gases in astrophysics.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".