On the Use of CHIME to Detect Long-duration Radio Transients from Neutron Star Mergers
Bibliographic record
Abstract
Abstract The short gamma-ray burst (SGRB) GRB 170817A was found to be related to a binary neutron star (BNS) merger. It is uncertain whether all SGRBs are caused by BNS mergers and also under what conditions a BNS merger can cause an SGRB. As BNS mergers can cause SGRBs, afterglow observations will also provide an alternative measurement of the BNS merger rate independent of gravitational-wave observations. In previous work by Feng et al., the feasibility of the detection of afterglows was considered using a variety of radio observatories and a simple flux threshold detection algorithm. Here, we consider a more sophisticated detection algorithm for SGRB afterglows and provide an estimate of the trials factors for a realistic search to obtain an updated estimate of the possibility of observing afterglows with the Canadian Hydrogen Intensity Mapping Experiment (CHIME). We estimate 893 and 312 afterglows per year can be detected using a 3σ confidence level threshold with two jet models, one with half-opening angle uniformly distributed in 6°–30° and the other uniformly distributed in 3°–8° with the median of 6°. We also find that 88% and 98%, respectively, of the detectable afterglows for each jet-opening distribution are off axis, which are candidates for orphan afterglows. Our result predicts fewer detectable sources per year than the earlier analysis but confirms the essential conclusion that using CHIME to search for afterglows will be effective in constraining the astrophysical merger rate.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".