The cosmic UV background and the beginning and end of star formation in simulated field dwarf galaxies
Bibliographic record
Abstract
ABSTRACT We use the APOSTLE cosmological simulations to examine the role of the cosmic UV background in regulating star formation (SF) in low-mass Lambda cold dark matter (ΛCDM) haloes. In agreement with earlier work, we find that after reionization SF proceeds mainly in haloes whose mass exceeds a redshift-dependent ‘critical’ mass, Mcrit, set by the structure of the haloes and by the thermal pressure of UV-heated gas. Mcrit increases from $\sim 10^{8}\, \mathrm{M}_\odot$ at z ∼ 10 to $M_{\rm crit}\sim 10^{9.7}\, \mathrm{M}_\odot$ at z = 0, roughly following the average mass growth of haloes in that mass range. This implies that haloes well above or below critical at present have remained so since early times. Haloes of luminous dwarfs today were already above-critical and star forming at high redshift, explaining naturally the ubiquitous presence of ancient stellar populations in dwarfs, regardless of luminosity. The SF history of systems close to the critical boundary is more complex. SF may cease or reignite in dwarfs whose host halo falls below or climbs above the critical boundary, suggesting an attractive explanation for the episodic nature of SF in some dwarfs. Also, some subcritical haloes today may have been above critical in the past; these systems should at present make up a sizable population of faint field dwarfs lacking ongoing star formation. Although few such galaxies are currently known, the discovery of this population would provide strong support for our results. Our work indicates that, rather than stellar feedback, it is the ionizing UV background and mass accretion history what regulates SF in the faintest dwarfs.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".