The determination of the three-dimensional (3D) geometry of coronal features is important for understanding the magnetic structuring of the solar atmosphere. In this context, the length of a coronal loop, which is subject to standing transverse oscillations, is a crucial parameter in coronal seismology for the correct estimation of the phase speed of the wave and, consequently, of the Alfven speed and coronal magnetic-field strength. Simultaneous space-based observations of the solar corona from different vantage points, e.g. one from the Solar Dynamics Observatory (SDO) and the second from the Solar TErrestrial RElations Observatory (STEREO), have permitted the reconstruction of the geometry of coronal loops. Nistico, Verwichte, and Nakariakov (Entropy15, 4520, 2013) proposed a method based on principal component analysis for fitting an ensemble of 3D points that sample a coronal loop. This method was shown to retrieve easily the main geometric parameters that define a loop, such as the loop axes and the loop plane. In this article, an extension of that work is presented that includes a Python tool for performing geometric triangulation of coronal features seen by two different observers.
Three-Dimensional Reconstruction of Coronal Features: A Python Tool for Geometric Triangulation
NISTICO' GIUSEPPE
Writing – Review & Editing
2023-01-01
Abstract
The determination of the three-dimensional (3D) geometry of coronal features is important for understanding the magnetic structuring of the solar atmosphere. In this context, the length of a coronal loop, which is subject to standing transverse oscillations, is a crucial parameter in coronal seismology for the correct estimation of the phase speed of the wave and, consequently, of the Alfven speed and coronal magnetic-field strength. Simultaneous space-based observations of the solar corona from different vantage points, e.g. one from the Solar Dynamics Observatory (SDO) and the second from the Solar TErrestrial RElations Observatory (STEREO), have permitted the reconstruction of the geometry of coronal loops. Nistico, Verwichte, and Nakariakov (Entropy15, 4520, 2013) proposed a method based on principal component analysis for fitting an ensemble of 3D points that sample a coronal loop. This method was shown to retrieve easily the main geometric parameters that define a loop, such as the loop axes and the loop plane. In this article, an extension of that work is presented that includes a Python tool for performing geometric triangulation of coronal features seen by two different observers.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.