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New Insights on Gamma-Ray Burst Radiation Mechanisms from Multiwavelength Observations
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作者 Yu-Hua Yao fang-sheng min +1 位作者 Shi Chen Yi-Qing Guo 《Research in Astronomy and Astrophysics》 2025年第2期1-10,共10页
The study of high-energy gamma-ray emission from gamma-ray bursts(GRBs)involves complex synchrotron radiation and synchrotron self-Compton(SSC)scattering mechanisms with multiple parameters exhibiting a wide distribut... The study of high-energy gamma-ray emission from gamma-ray bursts(GRBs)involves complex synchrotron radiation and synchrotron self-Compton(SSC)scattering mechanisms with multiple parameters exhibiting a wide distribution.Recent advancements in GRB research,particularly the observation of very high energy(VHE,>100 Ge V)radiation,have ushered in a new era of multiwavelength exploration,offering fresh perspectives and limitations for understanding GRB radiation mechanisms.This study aimed to leverage VHE observations to refine constraints on synchrotron+SSC radiation from electrons accelerated by forward shocks.By analyzing two external environments—the uniform interstellar medium and stratified stellar wind medium,we conducted spectral and variability fitting for five specific bursts(GRB 180720B,GRB 190114C,GRB 190829A,GRB 201216C,and GRB 221009A)to identify the optimal parameters characterizing these events.A comparative analysis of model parameter distributions with and without VHE radiation observations reveals that the magnetic energy equipartition factorεBis more concentrated with VHE emissions.This suggests that VHE emissions may offer greater constraints on this microphysical parameter.Additionally,we found that the energy budget between VHE and ke V–Me Vγ-ray emissions under the SSC radiation exhibits an almost linear relationship,which may serve as a tool to differentiate radiation mechanisms.We anticipate future statistical analyses of additional VHE bursts to validate our findings. 展开更多
关键词 (transients:)gamma-ray bursts radiation mechanisms:non-thermal gamma-rays:ISM
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Application of deep learning methods combined with physical background in wide field of view imaging atmospheric Cherenkov telescopes
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作者 Ao-Yan Cheng Hao Cai +25 位作者 Shi Chen Tian-Lu Chen Xiang Dong You-Liang Feng Qi Gao Quan-Bu Gou Yi-Qing Guo Hong-Bo Hu ming-ming Kang Hai-Jin Li Chen Liu Mao-Yuan Liu Wei Liu fang-sheng min Chu-Cheng Pan Bing-Qiang Qiao Xiang-Li Qian Hui-Ying Sun Yu-Chang Sun Ao-Bo Wang Xu Wang Zhen Wang Guang-Guang Xin Yu-Hua Yao Qiang Yuan Yi Zhang 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2024年第4期208-220,共13页
The High Altitude Detection of Astronomical Radiation(HADAR)experiment,which was constructed in Xizang,China,combines the wide-angle advantages of traditional EAS array detectors with the high-sensitivity advantages o... The High Altitude Detection of Astronomical Radiation(HADAR)experiment,which was constructed in Xizang,China,combines the wide-angle advantages of traditional EAS array detectors with the high-sensitivity advantages of focused Cherenkov detectors.Its objective is to observe transient sources such as gamma-ray bursts and the counterparts of gravitational waves.This study aims to utilize the latest AI technology to enhance the sensitivity of HADAR experiments.Training datasets and models with distinctive creativity were constructed by incorporating the relevant physical theories for various applications.These models can determine the type,energy,and direction of the incident particles after careful design.We obtained a background identification accuracy of 98.6%,a relative energy reconstruction error of 10.0%,and an angular resolution of 0.22°in a test dataset at 10 TeV.These findings demonstrate the significant potential for enhancing the precision and dependability of detector data analysis in astrophysical research.By using deep learning techniques,the HADAR experiment’s observational sensitivity to the Crab Nebula has surpassed that of MAGIC and H.E.S.S.at energies below 0.5 TeV and remains competitive with conventional narrow-field Cherenkov telescopes at higher energies.In addition,our experiment offers a new approach for dealing with strongly connected,scattered data. 展开更多
关键词 VHE gamma-ray astronomy HADAR Deep learning Convolutional neural networks
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