Constraining Warm Dark Matter and Population III Stars with the Global 21 cm Signal
Bibliographic record
Abstract
Abstract Upcoming ground- and space-based experiments may have sufficient accuracy to place significant constraints upon high-redshift star formation, Reionization, and dark matter (DM) using the global 21 cm signal of the intergalactic medium. In the early universe, when the relative abundance of low-mass DM halos was important, measuring the global signal would place constraints on the damping of structure formation caused by DM having a higher relic velocity (warm dark matter, or WDM) than in cold dark matter. Such damping, however, can be mimicked by altering the star formation efficiency (SFE) and can be difficult to detect because of the presence of Population III stars with unknown properties. We study these various cases and their degeneracies with the WDM mass parameter m X using a Fisher matrix analysis. We study the m X = 7 keV case and a star formation model that parameterizes the SFE as a strong function of halo mass and include several variations of this model along with three different input noise levels for the likelihood; we also use a minimum halo virial temperature for collapse near the molecular cooling threshold. We find that when the likelihood includes only Population II stars, m X is constrained to an uncertainty of ∼0.4 keV for all models and noise levels at the 68% confidence level. When the likelihood includes weak Population III stars, m X ∼ 0.3 keV, and if Population III star formation is relatively efficient, m X ∼ 0.1 keV uncertainty, with tight Population III star formation parameter constraints. Our results show that the global 21 cm signal is a promising test-bed for WDM models, even in the presence of strong degeneracies with astrophysical parameters.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".