The infrared luminosity of retired and post-starburst galaxies: A cautionary tale for star formation rate measurements
Bibliographic record
Abstract
In galaxies with significant ongoing star formation there is an impressively tight correlation between total infrared luminosity (L) and H <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>α</mml:mi> </mml:math> luminosity (L), when H <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>α</mml:mi> </mml:math> is properly corrected for stellar absorption and dust attenuation. This long-standing result gives confidence that both measurements provide accurate estimates of a galaxy’s star formation rate (SFR), despite their differing origins. To test the extent to which this holds in galaxies with lower specific SFR (sSFR=SFR/Mgal, where Mgal is the stellar mass), we combine optical spectroscopy from the Sloan Digital Sky Survey (SDSS) with multi-wavelength (FUV to FIR) photometric observations from the Galaxy And Mass Assembly survey (GAMA). We find that L/Lincreases steadily with decreasing H <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>α</mml:mi> </mml:math> equivalent width (W, a proxy for sSFR), indicating that both luminosities cannot provide a valid measurement of SFR in galaxies below the canonical star-forming sequence. For both ‘retired galaxies’ and ‘post-starburst galaxies’, L/L can be up to a factor of 30 larger than for star-forming galaxies. The smooth change in L/L, irrespective of star formation history, ionisation or heating source, dust temperature or other properties, suggests that the value of L/L is determined by the balance between star-forming regions and ambient interstellar medium contributing to both L and L. It is not a result of the differing timescales of star formation that these luminosities probe. While L can only be used to estimate the SFR for galaxies with W > 3 A (sSFR <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo>≳</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>11.5</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> /yr), we argue that the mid- and far-infrared can only be used to estimate the SFR of galaxies on the star-forming sequence, and in particular only for galaxies with W >10 A (sSFR <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo>≳</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>10.5</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> /yr). We find no evidence for dust obscured star-formation in local post-starburst 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 | 0.052 | 0.168 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.011 | 0.006 |
| Research integrity | 0.005 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".