Constraining the Earth-mass Primordial Black Hole Mergers Model of the Non-repeating FRBs Using the First CHIME/FRB Catalog
Bibliographic record
Abstract
Abstract In this paper, we upgrade the constraints for the Earth-mass primordial black hole mergers model based on the first Canadian Hydrogen Intensity Mapping Experiment (CHIME)/fast radio burst (FRB) catalog. Assuming the null hypothesis that the observed non-repeating FRBs originate from Earth-mass primordial black hole mergers, we find that how the charges were distributed in the primordial black hole population is well described by a double power-law function with typical charge value of q c / 10 − 5 = 1.60 − 0.28 + 0.28 , where the power-law index α 1 = 2.33 − 0.18 + 0.15 for q < q c and α 2 = 4.56 − 0.26 + 0.30 for q ≥ q c. Here, q represents the charge of the black hole in units of G M , where M is the mass of the black hole. Furthermore, we infer the local event rate of the bursts is 8.8 − 2.1 + 5.7 × 10 4 Gpc − 3 yr − 1 , which indicates that an abundance of the primordial black hole population f ≳ 10−4 is needed to account for the observed FRBs by CHIME. The results of this paper lay the basis for further research on the electromagnetic radiation background generated by the merger of primordial black hole mergers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".