多脉冲伽马射线暴的自组织临界性
Self-organized Criticality in Multi-pulse Gamma-Ray Bursts
摘要：
多脉冲伽马射线暴（GRB）的变化性可能有助于从中央引擎揭示潜在过程的机制。为了研究伽玛暴瞬发相是否存在自组织临界性（SOC）现象，我们采用马尔可夫链蒙特卡罗方法拟合了各向同性能量$E_{\rm iso}$、持续时间$T$和峰值计数率$P$等物理量的分布，统计研究了每个脉冲中有3个以上脉冲的伽玛暴的性质.我们的样本由CGRO/BATSE卫星观测到的93个伽玛暴中的454个脉冲组成。差分频率分布的这些幂律指数的最佳拟合值和不确定性是：$α^d_{E}=1.54 \pm 0.09$、$α^d_{T}=1.82_{-0.15}^{+0.14}$和$α^d_{P}=2.09_{-0.19}^{+0.18}$，而累积频率分布的幂律指数是：$α^c_{E}=1.44_{-0.10}^{+0.08}$、$α^c_{T}=1.75_{-0.13}^{+0.11}$和$α^c_{P}=1.99_{-0.19}^{+0.16}$。我们发现，这些分布是大致符合的物理框架的分形扩散，自组织临界性（FD-SOC）系统的空间维度$S=3$和经典的扩散$β$ =1。我们的研究结果支持，负责伽玛暴的喷流应该是磁主导的和磁不稳定性（例如，扭折模型，或撕裂模型不稳定性）导致GRB发射区进入SOC状态。
英文摘要：
The variability in multi-pulse gamma-ray bursts (GRBs) may help to reveal the mechanism of underlying processes from the central engine. To investigate whether the self-organized criticality (SOC) phenomena exist in the prompt phase of GRBs, we statistically study the properties of GRBs with more than 3 pulses in each burst by fitting the distributions of several observed physical variables with a Markov Chain Monte Carlo approach, including the isotropic energy $E_{\rm iso}$, the duration time $T$ and the peak count rate $P$ of each pulse. Our sample consists of 454 pulses in 93 GRBs observed by the CGRO/BATSE satellite. The best-fitting values and uncertainties for these power-law indices of the differential frequency distributions are: $α^d_{E}=1.54 \pm 0.09$, $α^d_{T}=1.82_{-0.15}^{+0.14}$ and $α^d_{P}=2.09_{-0.19}^{+0.18}$, while the power-law indices in the cumulative frequency distributions are: $α^c_{E}=1.44_{-0.10}^{+0.08}$, $α^c_{T}=1.75_{-0.13}^{+0.11}$ and $α^c_{P}=1.99_{-0.19}^{+0.16}$. We find that these distributions are roughly consistent with the physical framework of a Fractal-Diffusive, Self-Organized Criticality (FD-SOC) system with the spatial dimension $S=3$ and the classical diffusion $β$=1. Our results support that the jet responsible for the GRBs should be magnetically dominated and magnetic instabilities (e.g., kink model, or tearing-model instability) lead the GRB emission region into the SOC state.
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