THE PROPERTIES OF THE STAR-FORMING INTERSTELLAR MEDIUM AT<i>z</i>= 0.8–2.2 FROM HiZELS: STAR FORMATION AND CLUMP SCALING LAWS IN GAS-RICH, TURBULENT DISKS
Bibliographic record
Abstract
We present adaptive optics assisted integral field spectroscopy of nine Hα-selected galaxies at z = 0.84–2.23 drawn from the HiZELS narrowband survey. Our observations map the kinematics of these star-forming galaxies on ∼kpc scales. We demonstrate that within the interstellar medium of these galaxies, the velocity dispersion of the star-forming gas (σ) follows a scaling relation σ∝Σ 1/ n SFR + constant (where Σ SFR is the star formation surface density and the constant includes the stellar surface density). Assuming the disks are marginally stable (Toomre Q = 1), this follows from the Kennicutt–Schmidt relation (Σ SFR = A Σ n gas ), and we derive best-fit parameters of n = 1.34 ± 0.15 and A = 3.4 +2.5 −1.6 × 10 −4 M ☉ yr −1 kpc −2 , consistent with the local relation, and implying cold molecular gas masses of M gas = 10 9–10 M ☉ and molecular gas fractions of M gas /( M gas + M ⋆ ) = 0.3 ± 0.1, with a range of 10%–75%. We also identify 11 ∼kpc-scale star-forming regions (clumps) within our sample and show that their sizes are comparable to the wavelength of the fastest growing mode. The luminosities and velocity dispersions of these clumps follow the same scaling relations as local H ii regions, although their star formation densities are a factor ∼15 ± 5 × higher than typically found locally. We discuss how the clump properties are related to the disk, and show that their high masses and luminosities are a consequence of the high disk surface density.
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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 | 0.000 |
| 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) | 0.001 | 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".