Quantitative Image-Based Validation Framework for Assessing Global Coronal Magnetic Field Models

Abstract

Coronagraph observations provide key information about the orientation of the Sun's magnetic field. Previous studies used various algorithms to segment quasi-radial features in coronagraph images and approximate their local plane-of-sky geometry and orientation which can be used as input for optimizing and constraining coronal magnetic field models. We present a new framework that allows for further quantitative evaluations of image-based coronal segmentation methods against magnetic field models, and vice-versa. We compare quasi-radial features identified from QRaFT, a global coronal feature tracing algorithm, in white-light coronagraph images to outputs of MAS, an advanced magnetohydrodynamic model. We use the FORWARD toolset to produce synthetic polarized brightness images co-aligned to real coronagraph observations, segment features in these images, and quantify the difference between the inferred and model magnetic field. This approach allows us to geometrically compare features segmented in artificial images to those segmented in white-light coronagraph observations against the plane-of-sky projected MAS coronal magnetic field. We quantify QRaFT's performance in the artificial images and observational data, and perform statistical analyses that measure the accuracy and uncertainty of the model output to the observational data. The results demonstrate that a coronal segmentation method identifies the global large-scale orientation of the coronal magnetic field within $\sim \pm 10^{\circ }$ of the plane-of-sky projected MAS magnetic field.

26 pages, 11 figures, 4 tables. Accepted for publication in ApJ

References in corpus (16)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• Astropy: A Community Python Package for Astronomy
• Kernel density estimation via diffusion
• Alfven Wave Solar Model (AWSoM): Coronal Heating
• The solar magnetic field
• Validating a Time-Dependent Wave-Turbulence-Driven Model of the Solar Wind
• The role of Alfvén wave dynamics on the large scale properties of the solar wind: comparing an MHD simulation with PSP E1 data
• Towards a Realistic, Data-Driven Thermodynamic MHD Model of the Global Solar Corona
• Global Non-Potential Magnetic Models of the Solar Corona During the March 2015 Eclipse
• Closed-Field Coronal Heating Driven by Wave Turbulence
• Stray light and polarimetry considerations for the COSMO K-Coronagraph
• The Color and Brightness of the F-Corona Inferred from the 2019 July 2 Total Solar Eclipse
• The Solar Minimum Eclipse of 2019 July 2: II. The First Absolute Brightness Measurements and MHD Model Predictions of Fe X, XI and XIV out to 3.4 Rs
• Connecting the Low to High Corona: Propagating Disturbances as Tracers of the Near-Sun Solar Wind
• Tracking Non-Radial Outflows in Extreme Ultraviolet and White Light Solar Images
• Optimizing Global Coronal Magnetic Field Models Using Image-Based Constraints