Automated analysis of oscillations in coronal bright points
Automated analysis of oscillations in coronal bright points
复制标题
日冕亮点振荡的自动分析
DOI：
10.1051/0004-6361/202346757
复制
发表时间：
2023
影响因子：
6.5
通讯作者：
Ramsey B
中科院分区：
文献类型：
--
作者：
Ramsey B
日冕亮点(BPS)是在日冕中发现的众多明亮的小尺度动力学特征。亮点被观察到在广泛的周期内表现出强度振荡，很可能是等离子体加热和/或传输机制的重要标志。目的我们提出了一种新的、有效的基于小波的方法，该方法使用193ä带通中太阳动力学天文台(SDO)上的大气成像组件(AIA)的图像来自动检测和跟踪BPS的强度演变。通过对大量具有统计意义的二值图像的研究，我们试图对其潜在的物理机制施加约束。方法我们使用了二维连续小波变换(CWT)来检测图像中的二值图像。结果在4、8-10、17、28和65min有显著的周期性。亮点寿命服从指数−为1.13的 ± 为0.07的幂函数。BP寿命与最大直径之间的关系类似于指数为0.129 ± 0.011的幂函数关系。结论基于小波的方法成功地检测和提取了BP，并对其强度振荡进行了分析。未来的工作将使用更大的数据集和同时的多仪器观测来扩展这些方法。
ContextCoronal bright points (BPs) are numerous, bright, small-scale dynamical features found in the solar corona. Bright points have been observed to exhibit intensity oscillations across a wide range of periodicities and are likely an important signature of plasma heating and/or transport mechanisms.AimsWe present a novel and efficient wavelet-based method that automatically detects and tracks the intensity evolution of BPs using images from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) in the 193 Å bandpass. Through the study of a large, statistically significant set of BPs, we attempt to place constraints on the underlying physical mechanisms.MethodsWe used a continuous wavelet transform (CWT) in 2D to detect the BPs within images. One-dimensional CWTs were used to analyse the individual BP time series to detect significant periodicities.ResultsWe find significant periodicity at 4, 8–10, 17, 28, and 65 min. Bright point lifetimes are shown to follow a power law with exponent −1.13 ± 0.07. The relationship between the BP lifetime and maximum diameter similarly follows a power law with exponent 0.129 ± 0.011.ConclusionsOur wavelet-based method successfully detects and extracts BPs and analyses their intensity oscillations. Future work will expand upon these methods, using larger datasets and simultaneous multi-instrument observations.