来自 SGR J0501+4516 的 X 射线爆发中单个脉冲的综合定时分析

Jiao-Jiao Yang, Shuo Xiao, Zheng-Huo Jiang, Tong-Lei Liao, Mei-Xin Hong and Xi-Hong Luo
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摘要

来自软伽马射线中继器(SGR)的X射线暴(XRB)光曲中的脉冲一般被认为是由磁壳断裂或磁重联引起的,反映了磁星能量释放过程的演变。在这项研究中,我们对费米号伽马射线暴监测器探测到的来自SGR J0501+4156的27个XRB进行了全面的定时分析。利用改进的脉冲寻找算法,我们共识别出 95 个脉冲,并使用多个 FRED 函数对其进行拟合,从而获得基于马尔可夫链蒙特卡罗方法的脉冲形状参数。我们根据最短脉冲计算 XRB 的最小可变时标(MVTs);MVTs 的分布遵循对数高斯函数,均值为毫秒(1σ)。上升时间、衰减时间、等待时间、宽度、偏度和峰度的分布都遵循对数高斯函数,它们之间存在多种幂律依赖关系,例如,衰减时间和上升时间之间存在幂律正相关关系(4.7σ),脉冲宽度和峰度之间存在幂律负相关关系(6.8σ)。此外,脉冲数与脉冲串持续时间之间存在 3.7σ 的正相关。我们的研究结果倾向于磁层起源,与伽马射线暴的一些相似之处意味着它们有类似的辐射机制,如磁重联过程。
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A Comprehensive Timing Analysis of Individual Pulses in X-Ray Bursts from SGR J0501+4516
The pulses in X-ray-burst (XRB) light curves from soft gamma-ray repeaters (SGRs) are generally thought to arise from magnetic crustal fractures or magnetic reconnection, reflecting the evolution of the energy release process in magnetars. In this study, we conduct a comprehensive timing analysis of 27 XRBs from SGR J0501+4156 detected by the Gamma-ray Burst Monitor on board Fermi. Utilizing a improved pulse-finding algorithm, we identify a total of 95 pulses and fit them using multiple FRED functions to obtain pulse-shape parameters based on the Markov Chain Monte Carlo method. We calculate the minimum variability timescales (MVTs) of the XRBs based on the shortest pulse; the distribution of MVTs follows a log-Gaussian function with a mean of ms (1σ). The distributions of rise time, decay time, waiting time, width, skewness, and peakedness all follow the log-Gaussian function, and multiple power-law dependencies are observed between them; for example, a power-law positive correlation between decay time and rise time with 4.7σ, and a power-law negative correlation between pulse width and peakedness with 6.8σ. Besides, there is a positive correlation with 3.7σ between the number of pulses and burst duration. Our findings favor a magnetospheric origin, and some similarities with gamma-ray bursts imply that they have similar radiation mechanisms, e.g., magnetic reconnection processes.
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