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Investigating FRB 20240114A with FAST: Morphological Classification and Drifting Rate Measurements in a Burst-Cluster Framework

Long-Xuan Zhang, Shiyan Tian, Junyi Shen, Jun-Shuo Zhang, Dejiang Zhou, Lin Zhou, Po Ma, Tian-Cong Wang, Dengke Zhou, Jinlin Han, Yunpeng Men, Fayin Wang, Jiarui Niu, Pei Wang, Weiwei Zhu, Bing Zhang, Di Li, Yuan-Chuan Zou, Wei-Yang Wang, Yuan-Pei Yang, Qin Wu, He Gao, Ke-Jia Lee, Jia-Wei Luo, Rui Luo, Chao-Wei Tsai, Lin Lin, Wanjin Lu, Jintao Xie, Jianhua Fang, Jinhuang Cao, Chen-Chen Miao, Yuhao Zhu, Yunchuan Chen, Yong-Kun Zhang, Shuo Cao, Zi-Wei Wu, Chunfeng Zhang, Silu Xu, Huaxi Chen, Xiang-Lei Chen, Xianghan Cui, Yi Feng, Yu-Xiang Huang, Weicong Jing, Dong-Zi Li, Jian Li, Ye Li, Chen-Hui Niu, Yong-Feng Huang, Qingyue Qu, Yuanhong Qu, Bojun Wang, Yi-Dan Wang, Suming Weng, Xuefeng Wu, Heng Xu, Shihan Yew, Aiyuan Yang, Wenfei Yu, Lei Zhang, Rushuang Zhao

Abstract

This study investigates the morphological classification and drifting rate measurement of the repeating fast radio burst (FRB) source FRB 20240114A using the Five-hundred-meter Aperture Spherical Telescope (FAST). Detected on January 14, 2024, FRB 20240114A exhibited an exceptionally high burst rate, revealing unique properties. Through observational campaigns over several months, we selected a dataset comprising 3,203 bursts (2,109 burst-clusters) during a continuous monitoring session (15,780 seconds) on March 12, 2024. Improving upon previous work, we clarify the definitions of sub-bursts, bursts and burst-clusters. Using an average dispersion measures (DM) of 529.2 pc cm$^{-3}$, we classified the burst-clusters into Downward Drifting, Upward Drifting, No Drifting, No Evidence for Drifting, Not-Clear, and Complex burst-clusters. Among the 978 burst-clusters that exhibit drifting behavior, 233 (23.82%) show upward drifting. Additionally, if 142 upward drifting single-component burst-clusters are excluded, upward drifting double- and multi-component burst-clusters still account for 10.89% of the 836 burst-clusters exhibiting drifting behavior, equating to 91 burst-clusters. Furthermore, if only upward drifting burst-clusters with consecutive time intervals (or upward drifting bursts) are considered, only 9 bursts remain. Drifting rate comparisons with other physical quantities reveal that the drifting rate increases with peak frequency for single-component burst-clusters with drifting behavior. Moreover, in single-component burst-clusters, those with upward drifting exhibit smaller effective widths, bandwidths, and fluxes than their downward drifting counterparts. A Kolmogorov-Smirnov test further indicates that upward drifting burst-clusters possess longer consecutive time intervals than downward drifting ones, suggesting distinct underlying physical mechanisms.

Investigating FRB 20240114A with FAST: Morphological Classification and Drifting Rate Measurements in a Burst-Cluster Framework

Abstract

This study investigates the morphological classification and drifting rate measurement of the repeating fast radio burst (FRB) source FRB 20240114A using the Five-hundred-meter Aperture Spherical Telescope (FAST). Detected on January 14, 2024, FRB 20240114A exhibited an exceptionally high burst rate, revealing unique properties. Through observational campaigns over several months, we selected a dataset comprising 3,203 bursts (2,109 burst-clusters) during a continuous monitoring session (15,780 seconds) on March 12, 2024. Improving upon previous work, we clarify the definitions of sub-bursts, bursts and burst-clusters. Using an average dispersion measures (DM) of 529.2 pc cm, we classified the burst-clusters into Downward Drifting, Upward Drifting, No Drifting, No Evidence for Drifting, Not-Clear, and Complex burst-clusters. Among the 978 burst-clusters that exhibit drifting behavior, 233 (23.82%) show upward drifting. Additionally, if 142 upward drifting single-component burst-clusters are excluded, upward drifting double- and multi-component burst-clusters still account for 10.89% of the 836 burst-clusters exhibiting drifting behavior, equating to 91 burst-clusters. Furthermore, if only upward drifting burst-clusters with consecutive time intervals (or upward drifting bursts) are considered, only 9 bursts remain. Drifting rate comparisons with other physical quantities reveal that the drifting rate increases with peak frequency for single-component burst-clusters with drifting behavior. Moreover, in single-component burst-clusters, those with upward drifting exhibit smaller effective widths, bandwidths, and fluxes than their downward drifting counterparts. A Kolmogorov-Smirnov test further indicates that upward drifting burst-clusters possess longer consecutive time intervals than downward drifting ones, suggesting distinct underlying physical mechanisms.

Paper Structure

This paper contains 16 sections, 4 equations, 14 figures, 1 table.

Table of Contents

  1. Introduction
  2. Observations and burst-cluster Detection
  3. Data Analysis and Burst Detection
  4. DM Optimized for Structure
  5. burst-cluster Morphological Classification
  6. Downward Drifting burst-clusters
  7. Upward Drifting burst-clusters
  8. No Drifting burst-clusters
  9. burst-clusters with No Evidence for Drifting
  10. burst-clusters with Not-Clear
  11. Complex burst-clusters
  12. Statistical relations Between Drifting Rate and Other Physical Quantities
  13. Drifting Rate Analysis
  14. Statistical relations Between Peak Frequency, Drifting Rate, Bandwidth, Effective Width and Energy
  15. Analysis of consecutive and intermittent for downward and upward drifting
  16. ...and 1 more sections

Figures (14)

  • Figure 1: Comparison of two DM measurement methods, DM_phase and DM_power, applied to the data from March 12, 2024 (20240312). The left panel shows results from DM_phase, while the right panel corresponds to DM_power, both yielding consistent results. The dotted line indicates the average DM value, denoted by ⟨DM⟩, which is determined to be $529.2~\text{pc~cm}^{-3}$ for both DM_phase and DM_power, with the standard error (SE) reflecting the variability in the measurements. Only data points with error bars $< 1~\text{pc~cm}^{-3}$ (i.e., a one-sided error bar of $0.5~\text{pc~cm}^{-3}$) are plotted, selected from the original 3203 bursts, with the number of precise data points noted in Sample Count.
  • Figure 2: Both figures compare the DM_power results for two data sets: March 11 2024 session (20240311) and March 13 2024 session (20240313), obtained using the DM_power software. The average DM values for these two days are shown for comparison. Interestingly, the DM value for the March 12, 2024 (20240312) data lies precisely between the values of the March 11 and March 13 datasets, suggesting that the DM for this day is consistent with a midpoint between the two neighboring observations.
  • Figure 3: Illustration of the definitions for burst-clusters, bursts, sub-bursts, as well as consecutive and intermittent time intervals. $\tau$ represents the time valley in the waiting-time distribution, assuming 400 ms here. Burst-cluster A consists of three bursts, six sub-bursts, three consecutive time intervals, and two intermittent time intervals. Burst-cluster B, C, and D are similar, as shown in the figure. In this observation session, the total counts of burst-clusters, bursts, sub-bursts, consecutive time intervals, and intermittent time intervals are four, ten, fifteen, five, and six, respectively. The total time scale in the figure is in the order of seconds. Since the bursts are distributed on the millisecond scale and are far apart, the figure employs an exaggerated representation to make the millisecond-scale bursts more visible.
  • Figure 4: The typical dynamic spectra of downward drifting burst-clusters. Each burst-cluster is labeled as Dx-y, where x denotes the number of components. If the number of components exceeds two, x is noted as m. The y value indicates the observation band of the burst-cluster: L (low frequency), M (middle frequency), H (high frequency), W (wide frequency). The plots are arranged in a grid of four rows and three columns, with x corresponding to each column and y corresponding to each row.
  • Figure 5: The typical dynamic spectra of upward drifting burst-clusters. Each burst-cluster is labeled as Ux-y, where x denotes the number of components (labeled as 'm' if the number exceeds two), and y indicates the observation band: L (low frequency), M (middle frequency), H (high frequency), W (wide frequency). The plots are arranged in a grid of four rows and three columns, with x corresponding to each column and y corresponding to each row. Notably, our sample contains no events classified as Um-M or U1-W.
  • ...and 9 more figures