The effects of dark matter annihilation and dark matter-baryon velocity offsets at Cosmic Dawn
Bibliographic record
Abstract
Abstract Dark matter annihilation has the potential to leave an imprint on the properties of the first luminous structures at Cosmic Dawn as well as the overall evolution of the intergalactic medium (IGM). In this work, we employ a semi-analytic method to model dark matter annihilation during Cosmic Dawn (approximately redshift z = 20 to 40), examining potential modifications to IGM evolution as well as gas collapse, cooling, and star formation in mini-halos. Our analysis takes into account the effects of dark matter-baryon velocity offsets, utilizing the public 21cmvFAST code, and producing predictions for the 21cm global signal. The results from our simplified model suggest that dark matter annihilation can suppress the gas fraction in small halos and alter the molecular cooling process, while the impact on star formation might be positive or negative depending on parameters of the dark matter model as well as the redshift and assumptions about velocity offsets. This underscores the need for more comprehensive simulations of the effects of exotic energy injection at Cosmic Dawn as observational probes are providing us new insights into the process of reionization and the formation of first stars and 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 | 0.002 |
| 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 | 0.001 | 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".