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Solar Filament Physiognomy: Inferring Magnetic Quantities from Imaging Observations

P. F. Chen

TL;DR

This paper reviews solar filament physiognomy, a framework for inferring coronal magnetic properties from imaging observations rather than polarization data. It surveys imaging-based proxies for helicity sign, curvature radius, magnetic configuration, and twist strength, detailing methods such as fibril orientation, coronal cell plumes, thread skew, sigmoid shapes, barb bearing, and endpoint brightenings, and connecting these proxies to underlying magnetic topologies. A key result is that the curvature radius can be estimated from longitudinal filament oscillations using the pendulum model $P=2\pi\sqrt{R/g}$, and that filaments may be sustained by flux ropes or sheared arcades, with helicity-barb relationships providing indirect topology diagnostics. The work argues that advances in high-resolution imaging, especially with upcoming telescopes like DKIST, will enhance the diagnostic power of filament physiognomy and improve our understanding of eruption mechanisms and coronal magnetism.

Abstract

Magnetic field is the key physical quantity in solar physics as it controls all kinds of solar activity, ranging from nanoflares to big flares and coronal mass ejections (CMEs). However, so far only the magnetic field on the solar surface can be more or less precisely measured, and the most important coronal magnetic field remains undetectable accurately. Without the knowledge of the coronal magnetic field, it is even more difficult to obtain secondary quantities related to magnetic field, such as the magnetic helicity and magnetic configuration, including the curvature of field lines. The prevailing approaches to obtain the coronal magnetic field include coronal magnetic extrapolation and coronal seismology. Actually there were scattered efforts to derive secondary magnetic quantities based on imaging observations of solar filaments, without the help of polarization measurements. We call this approach solar filament physiognomy. In this paper, we review these efforts made in the past decades, and point out that this approach will be promising as large telescopes are being built and more fine structures of filament channels will be revealed.

Solar Filament Physiognomy: Inferring Magnetic Quantities from Imaging Observations

TL;DR

This paper reviews solar filament physiognomy, a framework for inferring coronal magnetic properties from imaging observations rather than polarization data. It surveys imaging-based proxies for helicity sign, curvature radius, magnetic configuration, and twist strength, detailing methods such as fibril orientation, coronal cell plumes, thread skew, sigmoid shapes, barb bearing, and endpoint brightenings, and connecting these proxies to underlying magnetic topologies. A key result is that the curvature radius can be estimated from longitudinal filament oscillations using the pendulum model , and that filaments may be sustained by flux ropes or sheared arcades, with helicity-barb relationships providing indirect topology diagnostics. The work argues that advances in high-resolution imaging, especially with upcoming telescopes like DKIST, will enhance the diagnostic power of filament physiognomy and improve our understanding of eruption mechanisms and coronal magnetism.

Abstract

Magnetic field is the key physical quantity in solar physics as it controls all kinds of solar activity, ranging from nanoflares to big flares and coronal mass ejections (CMEs). However, so far only the magnetic field on the solar surface can be more or less precisely measured, and the most important coronal magnetic field remains undetectable accurately. Without the knowledge of the coronal magnetic field, it is even more difficult to obtain secondary quantities related to magnetic field, such as the magnetic helicity and magnetic configuration, including the curvature of field lines. The prevailing approaches to obtain the coronal magnetic field include coronal magnetic extrapolation and coronal seismology. Actually there were scattered efforts to derive secondary magnetic quantities based on imaging observations of solar filaments, without the help of polarization measurements. We call this approach solar filament physiognomy. In this paper, we review these efforts made in the past decades, and point out that this approach will be promising as large telescopes are being built and more fine structures of filament channels will be revealed.

Paper Structure

This paper contains 13 sections, 1 equation, 11 figures.

Figures (11)

  • Figure 1: H$\alpha$ image of a quiescent filament with several barbs inside a filament channel observed by the New Vacuum Solar Telescope liuz14 on 2025 April 26. A collection of threads form the elongated filament spine with several barbs. The northern direction is indicated by the thick arrow. The combed dark fibrils originating from the bright plagettes are mainly directed toward right in the northern side of the filament and are directed toward left in the southern side.
  • Figure 2: (a) A method to determine the axial magnetic field and the helicity sign by combining H$\alpha$ filtergrams and longitudinal magnetograms proposed by fouk71. (b) Sketch showing how the helicity sign can be determined by H$\alpha$ filtergrams only.
  • Figure 3: Examples showing how to determine the axial magnetic field and the helicity sign based on EUV images (top row) and longitudinal magnetograms (bottom row). Adapted from shee13. The dashed arrows in the top row indicate four coronal cells as examples, and the solid arrows in the bottom row indicate the deduced direction of the axial magnetic field of the filament channel.
  • Figure 4: Sketch showing how to determine the helicity sign based on the orientation of the higher thread ( red line) relative to the lower thread ( blue line) in a filament, a method proposed by chae00.
  • Figure 5: Determining the helicity sign based on the shape of sigmoids above active-region filaments: N-shaped sigmoids imply negative helicity and S-shaped sigmoids imply positive helicity. Adapted from pevt02.
  • ...and 6 more figures