Scintillometry of fast radio bursts
Bibliographic record
Abstract
Fast radio bursts (FRBs) exhibit scintillation and scattering, which are often attributed to interactions with plasma screens in the Milky Way and the host galaxy. When these two screens appear “point-like” to each other, two scales of scintillation can be observed with sufficient frequency resolution. A screen perceives a second screen as extended or resolved when the angular size of the latter is smaller than the angular resolution of the former. The ratio of these two quantities is defined as the resolution power (RP). Previous observational studies have argued that, in the resolving regime, scintillations disappear, assuming that a screen resolving another screen is equivalent to a screen resolving an incoherent emission region. In this theoretical and simulation-based study of resolving effects in two-screen scenarios, we argue that resolving quenches only the relatively broad-scale scintillation and that this quenching is a gradual process. We present qualitative and quantitative predictions for dynamic spectra, spectral autocorrelation functions (ACFs), and modulation indices in resolved and unresolved regimes of two-screen systems. We show that the spectral ACFs of a two-screen system has a product term in addition to the sum of individual screen contributions, causing the total modulation index to rise to √3 in the unresolved regime. To aid in discovering resolving systems, we also present observable trends in multi-frequency observations of a screen resolving another screen or incoherent emission. Additionally, we introduce a new formula to estimate the distance between the FRB and the screen in its host galaxy. We also show that this formula, as with previous ones in the literature, is only applicable to screens that are two-dimensional in the plane of the sky.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".