Fitting an Analytic Magnetic Field to a Prestellar Core
Bibliographic record
Abstract
We deploy and demonstrate the capabilities of the magnetic field model developed by Ewertowski & Basu by fitting observed polarimetry data of the prestellar core FeSt 1-457. The analytic hourglass magnetic field function derived directly from Maxwell's equations yields a central-to-surface magnetic field strength ratio in the equatorial plane, as well as magnetic field directions with relative magnitudes throughout the core. This fit emerges from a comparison of a single plane of the model with the polarization map that results from the integrated properties of the magnetic field and dust throughout the core. Importantly, our fit is independent of any assumed density profile of the core. We check the robustness of the fit by using the POLARIS code to create synthetic polarization maps that result from the integrated scattering and emission properties of the dust grains and their radiative transfer, employing an observationally motivated density profile. We find that the synthetic polarization maps obtained from the model also provide a good fit to the observed polarimetry. Our model fits the striking feature of significant curvature of magnetic field lines in the outer part of FeSt 1-457. Combined with independent column density estimates, we infer that the core of size R gas has a mildly supercritical mass-to-flux ratio and may have formed through dynamical motions starting from a significantly larger radius R. A breakdown of flux freezing through neutral-ion slip (ambipolar diffusion) could be responsible for effecting such a transition from a large-scale magnetic field structure to a more compact gas structure.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".