A z = 0 Multiwavelength Galaxy Synthesis. I. A WISE and GALEX Atlas of Local Galaxies
Bibliographic record
Abstract
Abstract We present an atlas of ultraviolet and infrared images of ∼15,750 local ( d ≲ 50 Mpc) galaxies, as observed by NASA’s Wide-field Infrared Survey Explorer ( WISE ) and Galaxy Evolution Explorer ( GALEX ) missions. These maps have matched resolution (FWHM 7.″5 and 15″), matched astrometry, and a common procedure for background removal. We demonstrate that they agree well with resolved intensity measurements and integrated photometry from previous surveys. This atlas represents the first part of a program (the z = 0 Multiwavelength Galaxy Synthesis) to create a large, uniform database of resolved measurements of gas and dust in nearby galaxies. The images and associated catalogs will be publicly available at the NASA/IPAC Infrared Science Archive. This atlas allows us estimate local and integrated star formation rates (SFRs) and stellar masses ( M ⋆ ) across the local galaxy population in a uniform way. In the appendix, we use the population synthesis fits of Salim et al. to calibrate integrated M ⋆ and SFR estimators based on GALEX and WISE . Because they leverage a Sloan Digital Sky Survey (SDSS)-based training set of >100,000 galaxies, these calibrations have high precision and allow us to rigorously compare local galaxies to SDSS results. We provide these SFR and M ⋆ estimates for all galaxies in our sample and show that our results yield a “main sequence” of star-forming galaxies comparable to previous work. We also show the distribution of intensities from resolved galaxies in NUV-to-WISE1 versus WISE1-to-WISE3 space, which captures much of the key physics accessed by these bands.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".