DELAYED STAR FORMATION IN ISOLATED DWARF GALAXIES:<i>HUBBLE SPACE TELESCOPE</i>STAR FORMATION HISTORY OF THE AQUARIUS DWARF IRREGULAR
Bibliographic record
Abstract
We have obtained deep images of the highly isolated ( d = 1 Mpc) Aquarius dwarf irregular galaxy (DDO 210) with the Hubble Space Telescope Advanced Camera for Surveys. The resulting color–magnitude diagram (CMD) reaches more than a magnitude below the oldest main-sequence turnoff, allowing us to derive the star formation history (SFH) over the entire lifetime of the galaxy with a timing precision of ≈10% of the lookback time. Using a maximum likelihood fit to the CMD we find that only ≈10% of all star formation in Aquarius took place more than 10 Gyr ago (lookback time equivalent to redshift z ≈ 2). The star formation rate increased dramatically ≈6–8 Gyr ago ( z ≈ 0.7–1.1) and then declined until the present time. The only known galaxy with a more extreme confirmed delay in star formation is Leo A, a galaxy of similar M H i / M ⋆ , dynamical mass, mean metallicity, and degree of isolation. The delayed stellar mass growth in these galaxies does not track the mean dark matter accretion rate from CDM simulations. The similarities between Leo A and Aquarius suggest that if gas is not removed from dwarf galaxies by interactions or feedback, it can linger for several gigayears without cooling in sufficient quantity to form stars efficiently. We discuss possible causes for the delay in star formation including suppression by reionization and late-time mergers. We find reasonable agreement between our measured SFHs and select cosmological simulations of isolated dwarfs. Because star formation and merger processes are both stochastic in nature, delayed star formation in various degrees is predicted to be a characteristic (but not a universal) feature of isolated small galaxies.
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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 | 0.000 | 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".