Strong outflows and inefficient star formation in the reionization-era ultrafaint dwarf galaxy Eridanus <scp>ii</scp>
Bibliographic record
Abstract
ABSTRACT We present novel constraints on the underlying galaxy formation physics (e.g. mass-loading factor, star formation history, and metal retention) at z ≳ 7 for the low-mass (M* ∼ 105 M⊙) Local Group ultrafaint dwarf galaxy (UFD) Eridanus ii (Eri ii). Using a hierarchical Bayesian framework, we apply a one-zone chemical evolution model to Eri ii’s CaHK-based photometric metallicity distribution function (MDF; [Fe/H]) and find that the evolution of Eri ii is well characterized by a short, exponentially declining star formation history ($\tau _\text{SFH}=0.39\pm _{0.13}^{0.18}$ Gyr), a low star formation efficiency ($\tau _\text{SFE}=27.56\pm _{12.92}^{25.14}$ Gyr), and a large mass-loading factor ($\eta =194.53\pm _{42.67}^{33.37}$). Our results are consistent with Eri ii forming the majority of its stars before the end of reionization. The large mass-loading factor implies strong outflows in the early history of Eri ii and is in good agreement with theoretical predictions for the mass scaling of galactic winds. It also results in the ejection of >90 per cent of the metals produced in Eri ii. We make predictions for the distribution of [Mg/Fe]–[Fe/H] in Eri ii as well as the prevalence of ultra metal-poor stars, both of which can be tested by future chemical abundance measurements. Spectroscopic follow-up of the highest metallicity stars in Eri ii ([Fe/H] > −2) will greatly improve model constraints. Our new framework can readily be applied to all UFDs throughout the Local Group, providing new insights into the underlying physics governing the evolution of the faintest galaxies in the reionization era.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".