Primordial black hole dark matter in the context of extra dimensions
Bibliographic record
Abstract
Theories of large extra dimensions (LEDs) such as the Arkani-Hamed, Dimopoulos and Dvali scenario predict a ``true'' Planck scale ${M}_{\ensuremath{\star}}$ near the TeV scale, while the observed ${M}_{pl}$ is due to the geometric effect of compact extra dimensions. These theories allow for the creation of primordial black holes (PBHs) in the early Universe, from the collisional formation and subsequent accretion of black holes in the high-temperature plasma, leading to a novel cold dark matter (sub)component. Because of their existence in a higher-dimensional space, the usual relationship between mass, radius, and temperature is modified, leading to distinct behavior with respect to their four-dimensional counterparts. Here, we derive the cosmological creation and evolution of such PBH candidates, including the graybody factors describing their evaporation, and obtain limits on LED PBHs from direct observation of evaporation products, effects on big bang nucleosynthesis, and the cosmic microwave background angular power spectrum. Our limits cover scenarios of two to six extra dimensions, and PBH masses ranging from 10 to ${10}^{21}\text{ }\text{ }\mathrm{g}$. We find that for two extra dimensions, LED PBHs represent a viable dark matter candidate with a range of possible black hole masses between ${10}^{17}$ and ${10}^{23}\text{ }\text{ }\mathrm{g}$ depending on the Planck scale and reheating temperature. For ${M}_{\ensuremath{\star}}=10\text{ }\text{ }\mathrm{TeV}$, this corresponds to PBH dark matter with a mass of $M\ensuremath{\simeq}{10}^{21}\text{ }\text{ }\mathrm{g}$, unconstrained by current observations. We further refine and update constraints on ``ordinary'' four-dimensional black holes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".