The anatomy of a star-forming galaxy II: FUV heating via dust
Bibliographic record
Abstract
ABSTRACT Far-ultraviolet (FUV) radiation greatly exceeds UV, supernovae (SNe), and winds in the energy budget of young star clusters but is poorly modelled in galaxy simulations. We present results of the first isolated galaxy disc simulations to include photoelectric heating of gas via dust grains from FUV radiation self-consistently, using a ray-tracing approach that calculates optical depths along the source–receiver sightline. This is the first science application of the TREVR radiative transfer algorithm. We find that FUV radiation alone cannot regulate star formation. However, FUV radiation produces warm neutral gas and is able to produce regulated galaxies with realistic scale heights. FUV is also a long-range feedback and is more important in the outer discs of galaxies. We also use the superbubble feedback model, which depends only on the SN energy per stellar mass, is more physically realistic than common, parameter-driven alternatives and thus better constrains SN feedback impacts. FUV and SNe together can regulate star formation without producing too much hot ionized medium and with less disruption to the interstellar medium compared to SNe alone.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".