Ghostly stellar haloes and their relationship to ultrafaint dwarfs
Bibliographic record
Abstract
ABSTRACT Ghostly stellar haloes are extended haloes of stars composed solely of debris of pre-reionization fossil galaxies and should exist in dwarf galaxies with total masses <1010 M⊙. Fossil galaxies are even smaller mass dwarf galaxies that stopped forming stars after the epoch of reionization and have been identified in the Local Group as the ultrafaint dwarf satellites. Using cosmological N-body simulations, we present an empirical model for the shape and mass of ghostly stellar haloes. We compare the model to available observations of stellar haloes in six isolated dwarf galaxies in the Local Group (Leo T, Leo A, IC 10, WLM, IC 1613, NGC 6822) to infer the star formation efficiency in dwarf galaxies at the epoch of reionization. We find an efficiency of star formation in dark matter haloes with masses 106−108 M⊙ at z ∼ 7 in rough agreement with independent methods using data on the luminosity function of ultrafaint dwarf galaxies but systematically higher by a factor of 3–5. The systematic uncertainty of our results is still large, mainly because available observations of stellar halo profiles do not extend over a sufficiently large distance from the centre of the host dwarf galaxy. Additional observations, easily within reach of current telescopes, can significantly improve the accuracy of this method and can also be used to constrain the present-day dark matter masses of dwarf galaxies in the Local Group. Our method is based on a set of observations never used before; hence, it is a new independent test of models of hierarchical galaxy formation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".