Understanding star formation on the largest scales using the smallest galaxies: a statistical approach
Bibliographic record
Abstract
Globular clusters (GCs) are some of the oldest stellar populations in the universe. Their formation and evolution is deeply intertwined with that of their host galaxies, evidenced through a remarkably tight scaling relation between galaxy masses and the counts or masses of their GC populations. While this relation is well characterized for large galaxies, it is poorly constrained for dwarfs. Despite this, the simpler evolutionary histories and old, metal-poor stellar populations of dwarf galaxies make them a sort of “fossil” of early times, and therefore a promising venue in which to use GCs to learn about high-z star formation. This thesis utilizes empirical statistical models to characterize the massive star clusters of nearby dwarf galaxies and further our knowledge of large bursts of star formation in the high-z universe. The first project develops a hierarchical, errors-in-variables hurdle model (the HERBAL model) for the galaxy - GC scaling relation, which allows for the incorporation of galaxies without GCs. We find a wide mass transition region of 4 dex within which some galaxies host GCs while others lack them, and measure intrinsic scatter of $0.59$ dex. The second project applies the HERBAL model framework to young massive clusters (YMCs), the best local analogs to GCs. We find that, at a given stellar mass: (1) dwarf galaxies have more mass in GCs than in YMCs, and (2) a higher percentage of galaxies have GCs than YMCs. Evolutionary effects should cause these discrepancies to widen as the YMCs age into GC-like objects, implying that conditions in the early universe were far more favorable to large star cluster formation. The third project investigates the use of count models to describe the scaling relation between galaxy mass and number of GCs. We find that GC counts are not Poissonian nor zero-inflated, but are well described by a negative binomial regression. This suggests that GC formation is an extension of normal star formation, and that galaxies that lack GCs are not fundamentally different. These results can soon be directly tested with high-z observations, unlocking a more complete picture of star cluster formation and evolution across cosmic time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".