Validating the sub-burst slope law: a comprehensive multisource spectro-temporal analysis of repeating fast radio bursts

Author:

Brown Katie1,Chamma Mohammed A2ORCID,Rajabi Fereshteh2,Kumar Aishwarya1,Rajabi Hosein3,Houde Martin1ORCID

Affiliation:

1. Department of Physics and Astronomy, The University of Western Ontario , 1151 Richmond Street, London, Ontario N6A 3K7 , Canada

2. Department of Physics and Astronomy, McMaster University , 1280 Main Street West, Hamilton, Ontario L8S 4L8 , Canada

3. Department of Computer Science, The University of Western Ontario , 1151 Richmond Street, London, Ontario N6A 3K7 , Canada

Abstract

ABSTRACT We conduct a comprehensive spectro-temporal analysis of repeating fast radio bursts (FRBs) utilizing nine distinct sources, the largest sample to date. Our data set includes 175 sub-bursts and 31 multicomponent bursts from 11 data sets, with centre frequencies ranging from 149 to 7144  MHz and durations spanning from 73 µs to 13 ms. Our findings are consistent with the predictions of the triggered relativistic dynamical model (TRDM) of FRB emission. We affirm the predicted quadratic relationship between sub-burst slope and central frequency, as well as a linear dependence of the sub-burst bandwidth on central frequency that is consistent with mildly relativistic Doppler broadening of narrow-band emission. Most importantly, we confirm the sub-burst slope law, a predicted inverse relationship between sub-burst slope and duration, to hold consistently across different sources. Remarkably, we also discover that the drift rates of multicomponent bursts follow the same law as the sub-burst slopes, an unexplained result that warrants further investigation. These findings not only support the TRDM as a viable framework for explaining several aspects of FRB emission, but also provide new insights into the complex spectro-temporal properties of FRBs.

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Oxford University Press (OUP)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Positive and unlabelled machine learning reveals new fast radio burst repeater candidates;Monthly Notices of the Royal Astronomical Society;2024-08-15

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