Resolving the Formation of Cold H i Filaments in the High-velocity Cloud Complex C
Bibliographic record
Abstract
Abstract The physical properties of galactic halo gas have a profound impact on the life cycle of galaxies. As gas travels through a galactic halo, it undergoes dynamical interactions, influencing its impact on star formation and the chemical evolution of the galactic disk. In the Milky Way halo, considerable effort has been made to understand the spatial distribution of neutral gas, which is mostly in the form of large complexes. However, the internal variations of their physical properties remain unclear. In this study, we investigate the thermal and dynamical state of the neutral gas in high-velocity clouds. High-resolution observations (1.′1) of the 21 cm line emission in the EN field of the DHIGLS H i survey are used to analyze the physical properties of the bright concentration CIB located at an edge of a large HVC complex, complex C. We use the Gaussian decomposition code ROHSA to model the multiphase content of CIB and perform a power spectrum analysis to analyze its multiscale structure. The physical properties of some 200 structures extracted using dendrograms are examined. Each phase exhibits different thermal and turbulent properties. We identify two distinct regions, one of which has a prominent protrusion extending from the edge of complex C that exhibits an ongoing phase transition from warm diffuse gas to cold dense gas and filaments. The scale at which the warm gas becomes unstable and undergoes thermal condensation is about 15 pc, corresponding to a cooling time of about 1.5 Myr. Our study characterizes the statistical properties of turbulence in the fluid of an HVC for the first time. We find that a transition from subsonic to transonic turbulence is associated with the thermal condensation, going from large to small scales. A large-scale perspective of complex C suggests that hydrodynamic instabilities are involved in creating the structured concentration CIB and the phase transition therein. However, the details of the dynamical and thermal processes remain unclear and will require further investigation through both observations and numerical simulations.
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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 | 0.001 |
| 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".