Effects of dust absorption on spectroscopic studies of turbulence
Bibliographic record
Abstract
We study the effect of dust absorption on the recovery velocity and density spectra as well as on the anisotropies of magnetohydrodynamic turbulence using the velocity channel analysis (VCA), velocity coordinate spectrum (VCS) and velocity centroids. The dust limits volume up to an optical depth of unity. We show that in the case of the emissivity proportional to the density of emitters, the effects of random density get suppressed for strong dust absorption intensity variations arise from the velocity fluctuations only. However, for the emissivity proportional to squared density, both density and velocity fluctuations affect the observed intensities. We predict a new asymptotic regime for the spectrum of fluctuations for large scales exceeding the physical depths to unit optical depth. The spectrum gets shallower by unity in this regime. In addition, the dust absorption removes the degeneracy resulted in the universal K−3 spectrum of intensity fluctuations of self-absorbing medium reported by Lazarian & Pogosyan. We show that the predicted result is consistent with the available H ii region emission data. We find that for sub-Alfvénic and trans-Alfvénic turbulence one can get the information about both the magnetic field direction and the fundamental Alfvén, fast and slow modes that constitute MHD turbulence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".