LOFAR constraints on the repetition and environments of CHIME FRBs
Bibliographic record
Abstract
ABSTRACT The behaviour of fast radio bursts (FRBs) at radio frequencies $< 400$ MHz is poorly understood, with only two sources detected below 300 MHz. We robustly characterize the 150-MHz activity of CHIME-detected FRB sources relative to their 600-MHz activity – using their non-detection in 473 h of archival observations from the LOFAR Tied-Array All-Sky Survey (LOTAAS), and in 252 h of LOFAR observations of 14 repeating FRB sources – the largest sub-300 MHz targeted FRB campaign to date. We search the LOTAAS data for repeat bursts from 33 CHIME/FRB repeaters, 10 candidate repeaters, and 430 apparent non-repeaters. Their non-detection yields a population-level statistical spectral index constraint of $\alpha _{s, 135\, \rm {MHz}/600\, \rm {MHz}}>-0.9$, indicating that FRB spectral indices are, on average, flatter than those of pulsars. From the targeted campaign, the prolific repeater FRB 20201124A shows $\alpha _s>0.55$, implying reduced low-frequency activity, unlike the typically negative $\alpha _ \rm {s}$ seen from FRBs at higher frequency bands. We explore free–free absorption in its circumburst environment as a cause of the non-detection at 150 MHz, and find that it is consistent with either a very young $\sim 10$ yr old supernova remnant; or a typical H ii region. Our simulations indicate that LOFAR2.0 can detect 0.3–9 FRBs per week, with up to 4 FRBs originating from redshifts $1< z< 3$. Such detections will provide robust constraints on cosmological parameters due to their clean environments. Our results thus inform future low-frequency FRB searches through the limits we place on repetition rates and show how even non-detections can place meaningful constraints on FRB circumburst environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".