The Large Dispersion and Scattering of FRB 20190520B Are Dominated by the Host Galaxy
Bibliographic record
Abstract
Abstract The repeating fast radio burst FRB 20190520B is localized to a galaxy at z = 0.241, much closer than expected given its dispersion measure DM = 1205 ± 4 pc cm −3 . Here we assess implications of the large DM and scattering observed from FRB 20190520B for the host galaxy’s plasma properties. A sample of 75 bursts detected with the Five-hundred-meter Aperture Spherical radio Telescope shows scattering on two scales: a mean temporal delay τ (1.41 GHz) = 10.9 ± 1.5 ms, which is attributed to the host galaxy, and a mean scintillation bandwidth Δ ν d (1.41 GHz) = 0.21 ± 0.01 MHz, which is attributed to the Milky Way. Balmer line measurements for the host imply an H α emission measure (galaxy frame) EM s = 620 pc cm −6 × ( T /10 4 K) 0.9 , implying DM H α of order the value inferred from the FRB DM budget, DM h = 1121 − 138 + 89 pc cm −3 for plasma temperatures greater than the typical value 10 4 K. Combining τ and DM h yields a nominal constraint on the scattering amplification from the host galaxy F ˜ G = 1.5 − 0.3 + 0.8 ( pc 2 km ) − 1 / 3 , where F ˜ describes turbulent density fluctuations and G represents the geometric leverage to scattering that depends on the location of the scattering material. For a two-screen scattering geometry where τ arises from the host galaxy and Δ ν d from the Milky Way, the implied distance between the FRB source and dominant scattering material is ≲100 pc. The host galaxy scattering and DM contributions support a novel technique for estimating FRB redshifts using the τ –DM relation, and are consistent with previous findings that scattering of localized FRBs is largely dominated by plasma within host galaxies and the Milky Way.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".