Spatially resolved star formation and dust attenuation in Mrk 848: Comparison of the integral field spectra and the UV-to-IR SED
Bibliographic record
Abstract
We investigate the star formation history and the dust attenuation in the galaxy merger Mrk 848. Thanks to the multiwavelength photometry from the ultraviolet (UV) to the infrared (IR), and MaNGA’s integral field spectroscopy, we are able to study this merger in a detailed way. We divide the whole merger into the core and tail regions, and fit both the optical spectrum and the multi-band spectral energy distribution (SED) to models to obtain the star formation properties for each region respectively. We find that the color excess of stars in the galaxyE(B-V)sSEDmeasured with the multi-band SED fitting is consistent with that estimated both from the infrared excess (the ratio of IR to UV flux) and from the slope of the UV continuum. Furthermore, the reliability of theE(B-V)sSEDis examined with a set of mock SEDs, showing that the dust attenuation of the stars can be well constrained by the UV-to-IR broadband SED fitting. The dust attenuation obtained from optical continuumE(B-V)sspecis only about half ofE(B-V)sSED. The ratio of theE(B-V)sspecto theE(B-V)gobtained from the Balmer decrement is consistent with the local value (around 0.5). The difference between the results from the UV-to-IR data and the optical data is consistent with the picture that younger stellar populations are attenuated by an extra dust component from the birth clouds compared to older stellar populations which are only attenuated by the diffuse dust. Both with the UV-to-IR SED fitting and the spectral fitting, we find that there is a starburst younger than 100 Myr in one of the two core regions, consistent with the scenario that the interaction-induced gas inflow can enhance the star formation in the center of 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 | 0.001 |
| 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".