Thermal and Turbulent Properties of the Warm Neutral Medium in the Solar Neighborhood
Bibliographic record
Abstract
Abstract The transition from the diffuse warm neutral medium (WNM) to the dense cold neutral medium (CNM) is what set the initial conditions to the formation of molecular clouds. The properties of the turbulent cascade in the WNM, essential to describe this radiative condensation process, have remained elusive in part due to the difficulty in mapping out the structure and kinematics of each H i thermal phase. Here we present an analysis of a 21 cm hyper-spectral data cube from the GHIGLS H i survey where the contribution of the WNM is extracted using ROHSA, a Gaussian decomposition tool that includes spatial regularization. The distance and volume of the WNM emission is estimated using 3D dust extinction map information. The thermal and turbulent contributions to the Doppler line width of the WNM were disentangled using two techniques, one based on the statistical properties of the column density and centroid velocity fields, and the other on the relative motions of CNM structures as a probe of turbulent motions. We found that the volume of WNM sampled here (5.2 × 105 pc3), located at the outer edge of the Local Bubble, shows thermal properties in accordance with expected values for heating and cooling processes typical of the solar neighborhood: P th/k B = (4.4 ± 2.6) × 103 K cm−3, n = 0.74 ± 0.41 cm−3, and T k = (6.0 ± 1.3) × 103 K. The WNM has the properties of sub/trans-sonic turbulence, with a turbulent Mach number at the largest scale probed here (l = 130 pc) of , a density contrast of , and velocity and density power spectra compatible with k −11/3. The low Mach number of the WNM provides dynamical conditions that allow the condensation mode of thermal instability to grow freely and form CNM structures, as predicted by theory.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".