A<i>Far Ultraviolet Spectroscopic Explorer</i>Survey of Interstellar Molecular Hydrogen in the Small and Large Magellanic Clouds
Bibliographic record
Abstract
We describe a moderate-resolution Far Ultraviolet Spectroscopic Explorer ( FUSE ) survey of H 2 along 70 sight lines to the Small and Large Magellanic Clouds, using hot stars as background sources. FUSE spectra of 67% of observed Magellanic Cloud sources (52% of LMC and 92% of SMC) exhibit absorption lines from the H 2 Lyman and Werner bands between 912 and 1120 Å. Our survey is sensitive to N (H 2 ) ≥ 10 14 cm -2 ; the highest column densities are log N (H 2 ) = 19.9 in the LMC and 20.6 in the SMC. We find reduced H 2 abundances in the Magellanic Clouds relative to the Milky Way, with average molecular fractions = 0.010 for the SMC and = 0.012 for the LMC, compared with = 0.095 for the Galactic disk over a similar range of reddening. The dominant uncertainty in this measurement results from the systematic differences between 21 cm radio emission and Lyα in pencil beam sight lines as measures of N (H I). These results imply that the diffuse H 2 masses of the LMC and SMC are 8 × 10 6 and 2 × 10 6 M ☉ , respectively, 2% and 0.5% of the H I masses derived from 21 cm emission measurements. The LMC and SMC abundance patterns can be reproduced in ensembles of model clouds with a reduced H 2 formation rate coefficient, R ~ 3 × 10 -18 cm 3 s -1 , and incident radiation fields ranging from 10-100 times the Galactic mean value. We find that these high-radiation, low formation rate models can also explain the enhanced N (4)/ N (2) and N (5)/ N (3) rotational excitation ratios in the Clouds. We use H 2 column densities in low rotational states ( J = 0 and 1) to derive kinetic and/or rotational temperatures of diffuse interstellar gas, and we find that the distribution of rotational temperatures is similar to Galactic gas, with ⟨ T 01 ⟩ = 82 ± 21 K for clouds with N (H 2 ) ≥ 10 16.5 cm -2 . There is only a weak correlation between detected H 2 and far-infrared fluxes as determined by IRAS , perhaps as a result of differences in the survey techniques. We find that the surface density of H 2 probed by our pencil beam sight lines is far lower than that predicted from the surface brightness of dust in IRAS maps. We discuss the implications of this work for theories of star formation in low-metallicity environments.
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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 | 0.000 | 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".