Constraints on the distribution and energetics of fast radio bursts using cosmological hydrodynamic simulations
Bibliographic record
Abstract
We present constraints on the origins of fast radio bursts (FRBs) using large cosmological simulations. We calculate contributions to FRB dispersion measures (DMs) from the Milky Way, from the Local Universe, from cosmological large-scale structure, and from potential FRB host galaxies, and then compare these simulations to the DMs of observed FRBs. We find that the Milky Way contribution has previously been underestimated by a factor of ∼2, and that the foreground-subtracted DMs are consistent with a cosmological origin, corresponding to a source population observable to a maximum redshift z ∼ 0.6–0.9. We consider models for the spatial distribution of FRBs in which they are randomly distributed in the Universe, track the star formation rate of their host galaxies, track total stellar mass, or require a central supermassive black hole. Current data do not discriminate between these possibilities, but the predicted DM distributions for different models will differ considerably once we begin detecting FRBs at higher DMs and higher redshifts. We additionally consider the distribution of FRB fluences, and show that the observations are consistent with FRBs being standard candles, each burst producing the same radiated isotropic energy. The data imply a constant isotropic burst energy of ∼7 × 1040 erg if FRBs are embedded in host galaxies, or ∼9 × 1040 erg if FRBs are randomly distributed. These energies are 10–100 times larger than had previously been inferred. Within the constraints of the available small sample of data, our analysis favours FRB mechanisms for which the isotropic radiated energy has a narrow distribution in excess of 1040 erg.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".