Energy functions of fast radio bursts derived from the first CHIME/FRB catalogue
Bibliographic record
Abstract
ABSTRACT Fast radio bursts (FRBs) are mysterious millisecond pulses in radio, most of which originate from distant galaxies. Revealing the origin of FRBs is becoming central in astronomy. The redshift evolution of the FRB energy function, i.e. the number density of FRB sources as a function of energy, provides important implications for the FRB progenitors. Here, we show the energy functions of FRBs selected from the recently released Canadian Hydrogen Intensity Mapping Experiment (CHIME) catalogue using the Vmax method. The Vmax method allows us to measure the redshift evolution of the energy functions as it is without any prior assumption on the evolution. We use a homogeneous sample of 164 non-repeating FRB sources, which are about one order of magnitude larger than previously investigated samples. The energy functions of non-repeating FRBs show Schechter function-like shapes at z ≲ 1. The energy functions and volumetric rates of non-repeating FRBs decrease towards higher redshifts similar to the cosmic stellar-mass density evolution: there is no significant difference between the non-repeating FRB rate and cosmic stellar-mass density evolution with a 1 per cent significance threshold, whereas the cosmic star-formation rate scenario is rejected with a more than 99 per cent confidence level. Our results indicate that the event rate of non-repeating FRBs is likely controlled by old populations rather than young populations that are traced by the cosmic star-formation rate density. This suggests old populations, such as old neutron stars and black holes, as more likely progenitors of non-repeating FRBs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| 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) | 0.002 | 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".