论文标题
色球旋流I. H $α$观测值及其统计属性中的自动检测
Chromospheric swirls I. Automated detection in H$α$ observations and their statistical properties
论文作者
论文摘要
色球漩涡被认为在上太阳大气的动力学和加热中起着重要作用。重要的是在色球层观测中自动检测和跟踪它们并确定它们的性质。我们将最近开发的自动化色球漩涡检测方法应用于时间序列观测，对在瑞士1毫米太阳能望远镜上的Crisp仪器中通过CRISP仪器在H $-0.2Å波长H $-0.2Å波长中获得的太阳能球圈的安静区域。该算法利用了高对比度的色层观测值中旋转事件的形态特征，并导致在时间序列的每一帧中检测到这些结构及其随时间的跟踪。我们进行了统计分析以确定其各种特性，包括用于得出平均寿命的生存分析。在任何给定时间，在FOV中检测到平均146美元$ \ pm $ 9的漩涡。发现平均表面密度等于$ \ sim $ 0.08漩涡$ $ mm $ $^{ - 2} $，并且出现率为$ \ sim $ 10 $^{ - 2} $ swirls $ $ $ $ $ $ $ $^{ - 2} $ min $^min $^{ - 1} $。这些值远高于先前从色球观测结果报道的值。检测到的漩涡的半径在0.5至2.5毫米之间，平均值等于1.3 $ \ pm $ 0.3毫米，略高于以前的报告。寿命在1.5分钟至33.7分钟之间，算术平均值为$ \ sim $ 8.5分钟。然而，使用Kaplan-Meier估计器与参数模型的生存分析相结合，平均寿命为10.3 $ \ pm $ 0.6分钟。一种自动化的方法比视觉检查更多地阐明了它们的丰度，而更高的节奏，更高的分辨率观察很可能会导致在较小的尺度和寿命较短的情况下发现更高数量的此类功能。
Chromospheric swirls are considered to play a significant role in the dynamics and heating of the upper solar atmosphere. It is important to automatically detect and track them in chromospheric observations and determine their properties. We applied a recently developed automated chromospheric swirl detection method to time-series observations of a quiet region of the solar chromosphere obtained in the H$α$-0.2 Å wavelength of the H$α$ spectral line by the CRISP instrument at the Swedish 1-m Solar Telescope. The algorithm exploits the morphological characteristics of swirling events in high contrast chromospheric observations and results in the detection of these structures in each frame of the time series and their tracking over time. We conducted a statistical analysis to determine their various properties, including a survival analysis for deriving the mean lifetime. A mean number of 146 $\pm$ 9 swirls was detected within the FOV at any given time. The mean surface density is found equal to $\sim$0.08 swirls$ $Mm$^{-2}$ and the occurrence rate is $\sim$10$^{-2}$ swirls$ $Mm$^{-2}$ min$^{-1}$. These values are much higher than those previously reported from chromospheric observations. The radii of the detected swirls range between 0.5 and 2.5 Mm, with a mean value equal to 1.3 $\pm$ 0.3 Mm, which is slightly higher than previous reports. The lifetimes range between 1.5 min and 33.7 min with an arithmetic mean value of $\sim$8.5 min. A survival analysis of the lifetimes, however, using the Kaplan-Meier estimator in combination with a parametric model results in a mean lifetime of 10.3 $\pm$ 0.6 min. An automated method sheds more light on their abundance than visual inspection, while higher cadence, higher resolution observations will most probably result in the detection of a higher number of such features on smaller scales and with shorter lifetimes.
