An ALMA Survey of the SCUBA-2 Cosmology Legacy Survey UKIDSS/UDS Field: The Far-infrared/Radio Correlation for High-redshift Dusty Star-forming Galaxies
Bibliographic record
Abstract
Abstract We study the radio properties of 706 submillimeter galaxies (SMGs) selected at 870 μm with the Atacama Large Millimeter Array from the SCUBA-2 Cosmology Legacy Survey map of the Ultra Deep Survey field. We detect 273 SMGs at >4σ in deep Karl G. Jansky Very Large Array 1.4 GHz observations, of which a subset of 45 SMGs are additionally detected in 610 MHz Giant Metre-Wave Radio Telescope imaging. We quantify the far-infrared/radio correlation (FIRRC) through parameter q IR, defined as the logarithmic ratio of the far-infrared and radio luminosity, and include the radio-undetected SMGs through a stacking analysis. We determine a median q IR = 2.20 ± 0.03 for the full sample, independent of redshift, which places these z ∼ 2.5 dusty star-forming galaxies 0.44 ± 0.04 dex below the local correlation for both normal star-forming galaxies and local ultra-luminous infrared galaxies (ULIRGs). Both the lack of redshift evolution and the offset from the local correlation are likely the result of the different physical conditions in high-redshift starburst galaxies, compared to local star-forming sources. We explain the offset through a combination of strong magnetic fields (B ≳ 0.2 mG), high interstellar medium (ISM) densities and additional radio emission generated by secondary cosmic rays. While local ULIRGs are likely to have similar magnetic field strengths, we find that their compactness, in combination with a higher ISM density compared to SMGs, naturally explains why local and high-redshift dusty star-forming galaxies follow a different FIRRC. Overall, our findings paint SMGs as a homogeneous population of galaxies, as illustrated by their tight and nonevolving far-infrared/radio correlation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".