THE PANCHROMATIC HUBBLE ANDROMEDA TREASURY. VIII. A WIDE-AREA, HIGH-RESOLUTION MAP OF DUST EXTINCTION IN M31
Bibliographic record
Abstract
We map the distribution of dust in M31 at 25 pc resolution using stellar photometry from the Panchromatic Hubble Andromeda Treasury survey. The map is derived with a new technique that models the near-infrared color–magnitude diagram (CMD) of red giant branch (RGB) stars. The model CMDs combine an unreddened foreground of RGB stars with a reddened background population viewed through a log-normal column density distribution of dust. Fits to the model constrain the median extinction, the width of the extinction distribution, and the fraction of reddened stars in each 25 pc cell. The resulting extinction map has a factor of ≳4 times better resolution than maps of dust emission, while providing a more direct measurement of the dust column. There is superb morphological agreement between the new map and maps of the extinction inferred from dust emission by Draine et al. However, the widely used Draine & Li dust models overpredict the observed extinction by a factor of ∼2.5, suggesting that M31's true dust mass is lower and that dust grains are significantly more emissive than assumed in Draine et al. The observed factor of ∼2.5 discrepancy is consistent with similar findings in the Milky Way by the Plank Collaboration et al., but we find a more complex dependence on parameters from the Draine & Li dust models. We also show that the the discrepancy with the Draine et al. map is lowest where the current interstellar radiation field has a harder spectrum than average. We discuss possible improvements to the CMD dust mapping technique, and explore further applications in both M31 and other galaxies.
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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) | 0.003 | 0.001 |
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".