<i>Planck</i>early results. XXV. Thermal dust in nearby molecular clouds
Bibliographic record
Abstract
Planck allows unbiased mapping of Galactic sub-millimetre and millimetre emission from the most diffuse regions to the densest parts of molecular clouds. We present an early analysis of the Taurus molecular complex, on line-of-sight-averaged data and without component separation. The emission spectrum measured by Planck and IRAS can be fitted pixel by pixel using a single modified blackbody. Some systematic residuals are detected at 353 GHz and 143 GHz, with amplitudes around −7% and +13%, respectively, indicating that the measured spectra are likely more complex than a simple modified blackbody. Significant positive residuals are also detected in the molecular regions and in the 217 GHz and 100 GHz bands, mainly caused by the contribution of the J = 2 → 1 and J = 1 → 0 12CO and 13CO emission lines. We derive maps of the dust temperature T, the dust spectral emissivity index β, and the dust optical depth at 250 μm τ250. The temperature map illustrates the cooling of the dust particles in thermal equilibrium with the incident radiation field, from 16 − 17 K in the diffuse regions to 13 − 14 K in the dense parts. The distribution of spectral indices is centred at 1.78, with a standard deviation of 0.08 and a systematic error of 0.07. We detect a significant T − β anti-correlation. The dust optical depth map reveals the spatial distribution of the column density of the molecular complex from the densest molecular regions to the faint diffuse regions. We use near-infrared extinction and Hi data at 21-cm to perform a quantitative analysis of the spatial variations of the measured dust optical depth at 250 μm per hydrogen atom τ250/NH. We report an increase of τ250/NH by a factor of about 2 between the atomic phase and the molecular phase, which has a strong impact on the equilibrium temperature of the dust particles.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.063 | 0.033 |
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".