Non-ideal magnetohydrodynamic simulations of subcritical pre-stellar cores with non-equilibrium chemistry
Bibliographic record
Abstract
ABSTRACT Non-ideal magnetohydrodynamic (MHD) effects are thought to be gravity’s closest ally in overcoming the support of magnetic fields and in forming stars. Here, we modify the publicly available version of the adaptive mesh refinement code flash (Fryxell et al. 2000; Dubey et al. 2008) to include a detailed treatment of non-ideal MHD and study such effects in collapsing pre-stellar cores. We implement two very extended non-equilibrium chemical networks, the largest of which is comprised of ∼ 300 species and includes a detailed description of deuterium chemistry. The ambipolar diffusion, Ohmic and Hall resistivities are then self-consistently calculated from the abundances of charged species. We present a series of 2D axisymmetric simulations where we vary the chemical model, cosmic ray ionization rate, and grain distribution. We benchmark our implementation against ideal MHD simulations and previously published results. We show that, at high densities ($n_{\rm {H_2}}\gt ~10^6~\rm {cm^{-3}}$), the ion that carries most of the perpendicular and parallel conductivities is not $\rm {H_3^+}$ as was previously thought, but is instead $\rm {D_3^+}$.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".