Dispersion Distance and the Matter Distribution of the Universe in Dispersion Space
Bibliographic record
Abstract
We propose that "standard pings," brief broadband radio impulses, can be used to study the three-dimensional clustering of matter in the Universe even in the absence of redshift information. The dispersion of radio waves as they travel through the intervening plasma can, like redshift, be used as a cosmological distance measure. Because of inhomogeneities in the electron density along the line of sight, dispersion is an imperfect proxy for radial distance and we show that this leads to calculable dispersion-space distortions in the apparent clustering of sources. Fast radio bursts (FRBs) are a new class of radio transients that are the prototypical standard ping and, due to their high observed dispersion, have been interpreted as originating at cosmological distances. The rate of fast radio bursts has been estimated to be several thousand over the whole sky per day and, if cosmological, the sources of these events should trace the large-scale structure of the Universe. We calculate the dispersion-space power spectra for a simple model where electrons and FRBs are biased tracers of the large-scale structure of the Universe, and we show that the clustering signal could be measured using as few as 10 000 events. Such a survey is in line with what may be achieved with upcoming wide-field radio telescopes.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".