17 citations · 18 across the 6 of their papers we have counts for
5 papers · 1 filter
Estimating the peak energy of Swift gamma-ray bursts using supervised machine learning
Wan-Peng Sun, Si-Yuan Zhu, Da-Ling Ma +1
Gamma-ray bursts (GRBs) are among the most energetic explosive phenomena in the Universe, and their peak energy () is a key physical quantity for understanding the promp…
Unveiling the spectral morphological division of fast radio bursts with CHIME/FRB Catalog 2
Wan-Peng Sun, Yin-Long Cao, Yong-Kun Zhang +7
Fast radio bursts (FRBs) are commonly classified into repeating and apparently nonrepeating sources, yet whether this distinction reflects intrinsically different physical populati…
A Practical Framework for Estimating the Repetition Likelihood of Fast Radio Bursts from Spectral Morphology
Wan-Peng Sun, Yong-Kun Zhang, Ji-Guo Zhang +6
The repeating behavior of fast radio bursts (FRBs) is regarded as a key clue to understanding their physical origin, yet reliably distinguishing repeaters from apparent non-repeate…
Exploring the Key Features of Repeating Fast Radio Bursts with Machine Learning
Wan-Peng Sun, Ji-Guo Zhang, Yichao Li +4
Fast radio bursts (FRBs) are enigmatic high-energy events with unknown origins, which are observationally divided into two categories, i.e., repeaters and non-repeaters. However, t…
Classification of Fermi Gamma-Ray Bursts Based on Machine Learning
Si-Yuan Zhu, Wan-Peng Sun, Da-Ling Ma +1
Gamma-ray bursts (GRBs) are typically classified into long and short GRBs based on their durations. However, there is a significant overlapping in the duration distributions of the…