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arXiv · 2510.07002

Revealing the Temporally Stable Bimodal Energy Distribution of FRB 20121102A with a Tripled Burst Set from AI Detections

Abstract

Active repeating Fast Radio Bursts (FRBs), with their large number of bursts, burst energy distribution, and their potential energy evolution, offer critical insights into the FRBs emission mechanisms. Traditional pipelines search for bursts through conducting dedispersion trials and looking for signals above certain fluence thresholds, both of which could result in missing weak and narrow-band bursts. In order to improve the completeness of the burst set, we develop an End-to-end DedispersE-agnostic Nonparametric AI model (EDEN), which directly detect bursts from dynamic spectrum and is the first detection pipeline that operates without attempting dedispersion. We apply EDEN to archival FAST L-band observations during the extreme active phase of the repeating source FRB 20121102A, resulting in the largest burst set for any FRB to date, which contains 5,927 individual bursts, tripling the original burst set. The much enhanced completeness enables a refined analysis of the temporal behavior of energy distribution, revealing that the bimodal energy distribution remains stable over time. It is rather an intrinsic feature of the emission mechanisms than a consequence of co-evolving with burst rate.

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Yidan Wang, Jing Han, Pei Wang, Di Li, Hanting Chen, Yuchuan Tian, Erbil Gugercinoglu, Jianing Tang, Zihan Zhang, Kaichao Wu, Xiaoli Zhang, Yuhao Zhu, Jinhuang Cao, Mingtai Chen, Jiapei Feng, Zhaoyu Huai, Zitao Lin, Jieming Luan, Hongbin Wang, Junjie Zhao, Chaowei Tsai, Weiwei Zhu, Yongkun Zhang, Yi Feng, Aiyuan Yang, Dengke Zhou, Jianhua Fang, Jiaying Xu, Chenhui Niu, Jiarui Niu, Jumei Yao, Chunfeng Zhang, Rushuang Zhao, Lei Zhang, Junshuo Zhang, Wanjin Lu, Qingyue Qu. 2025-10-08. Revealing the Temporally Stable Bimodal Energy Distribution of FRB 20121102A with a Tripled Burst Set from AI Detections. https://arxiv.org/abs/2510.07002

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