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arXiv 2108.02624astro-ph.SR
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大气成像组合(AIA)数据中的尖峰分析

An Analysis of Spikes in Atmospheric Imaging Assembly (AIA) Data

Peter R. Young, Nicholeen M. Viall, Michael S. Kirk, Emily I. Mason, Lakshmi Pradeep Chitta

摘要:

太阳动力学天文台(SDO)上的大气成像组件(AIA)在七个极紫外(EUV)波长通道中返回太阳大气的高分辨率图像。这些图像在地面上进行处理,以消除高能粒子撞击仪器所产生的强度尖峰,并将消除尖峰的图像提供给社区。在这篇文章中,研究了2017年2月28日获得的来自171 A通道的三小时系列图像,以调查由太阳大气中的致密增亮引起的去峰算法误报的频率。后者通过连续三帧出现在同一探测器像素中的尖峰来识别。从900个图像帧中找到1096个示例。这些“三尖峰”被分配给126个动态太阳能功能,据估计,三尖峰方法确定的功能总数的20%受削峰。因此,对于任何10分钟的AIA 171 A图像序列,大约有35个太阳特征的强度被削弱。这些特征存在于活动区、平静太阳和冕洞,相对于太阳表面积,冕洞内的比例更大。在96%的情况下,despiked结构是一个紧凑的亮度大小为2弧秒或更少,其余的4%有狭窄,细长的结构。通过应用EUV突发检测算法,我们发现96%的事件可以归类为EUV突发。AIA处理流水线没有使尖峰事件变得不可见,但是事件的生命周期内的总强度可以降低高达67%。建议用户在研究表现出精细尺度结构的短暂或快速演变的特征时,始终将原始强度恢复到AIA数据。

英文摘要:

The Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) returns high-resolution images of the solar atmosphere in seven extreme ultraviolet (EUV) wavelength channels. The images are processed on the ground to remove intensity spikes arising from energetic particles hitting the instrument, and the despiked images are provided to the community. In this article a three-hour series of images from the 171 A channel obtained on 28 February 2017 was studied to investigate how often the despiking algorithm gave false positives caused by compact brightenings in the solar atmosphere. The latter were identified through spikes appearing in the same detector pixel for three consecutive frames. 1096 examples were found from the 900 image frames. These "three-spikes" were assigned to 126 dynamic solar features, and it is estimated that the three-spike method identifies 20% of the total number of features affected by despiking. For any ten-minute sequence of AIA 171 A images there are therefore around 35 solar features that have their intensity modified by despiking. The features are found in active regions, quiet Sun, and coronal holes and, in relation to solar surface area, there is a greater proportion within coronal holes. In 96% of the cases, the despiked structure is a compact brightening of size two arcsec or less and the remaining 4% have narrow, elongated structures. By applying an EUV burst detection algorithm, we found that 96% of the events could be classed as EUV bursts. None of the spike events are} rendered invisible by the AIA processing pipeline, but the total intensity over an event's lifetime can be reduced by up to 67%. Users are recommended to always restore the original intensities to AIA data when studying short-lived or rapidly evolving features that exhibit fine-scale structure.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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