论文标题
爆发过程中爆发过程的可变性签名
Variability Signatures of a Burst Process in Flaring Gamma-ray Blazars
论文作者
论文摘要
Blazars在电磁光谱上表现出随机通量变异性，通常表现出重尾通量分布，通常以对数正态建模。但是，Tavecchio等人。 （2020）和Adams等。 （2022）发现，几种最亮的Fermi-LAT平光谱类类产品（FSRQ）的高能量伽马射线通量分布（FSRQ）是通过更重的尾分布进行了很好的建模的，我们表明这是逆伽马分布。我们提出了一种自回旋反向伽马变异模型，其中射击过程是由于shot-noise过程而产生的。在此模型中，离散的爆发是单独解决的，并且在时间箱内平均，就像在Fermi-LAT数据的分析中一样。时间尺度上的随机变化长于时间bin持续时间的时间长，使用一阶自回归结构对时间量表进行建模。在许多弱爆发的限制情况下，通量分布大约变为对数正态。随着时间bin持续时间的增加，预计分数变异性会降低。使用模拟的光曲线，我们表明所提出的模型与FSRQ和BL LAC对象的典型伽马射线变异性属性一致。模型参数可以物理地解释为平均爆发速率，爆发和长期随机波动的时间尺度。
Blazars exhibit stochastic flux variability across the electromagnetic spectrum, often exhibiting heavy-tailed flux distributions, commonly modeled as lognormal. However, Tavecchio et al. (2020) and Adams et al. (2022) found that the high-energy gamma-ray flux distributions of several of the brightest flaring Fermi-LAT flat spectrum radio quasars (FSRQs) are well modeled by an even heavier-tailed distribution, which we show is the inverse gamma distribution. We propose an autoregressive inverse gamma variability model in which an inverse gamma flux distribution arises as a consequence of a shot-noise process. In this model, discrete bursts are individually unresolved and averaged over within time bins, as in the analysis of Fermi-LAT data. Stochastic variability on timescales longer than the time bin duration is modeled using first-order autoregressive structure. The flux distribution becomes approximately lognormal in the limiting case of many weak bursts. The fractional variability is predicted to decrease as the time bin duration increases. Using simulated light curves, we show that the proposed model is consistent with the typical gamma-ray variability properties of FSRQs and BL Lac objects. The model parameters can be physically interpreted as the average burst rate, the burst fluence, and the timescale of long-term stochastic fluctuations.
