Combining magneto-hydrostatic constraints with Stokes profiles inversions. III. Uncertainty in the inference of electric currents

Abstract

Electric currents play an important role in the energy balance of the plasma in the solar atmosphere. They are also indicative of non-potential magnetic fields and magnetic reconnection. Unfortunately, the direct measuring of electric currents has traditionally been riddled with inaccuracies. We study how accurately we can infer electric currents under different scenarios. We carry out increasingly complex inversions of the radiative transfer equation for polarized light applied to Stokes profiles synthesized from radiative three-dimensional magnetohydrodynamic (MHD) simulations. The inversion yields the magnetic field vector, $\mathbf{B}$, from which the electric current density, $\mathbf{j}$, is derived by applying Ampere's law. We find that the retrieval of the electric current density is only slightly affected by photon noise or spectral resolution. However, the retrieval steadily improves as the Stokes inversion becomes increasingly elaborated. In the least complex case (a Milne-Eddington-like inversion applied to a single spectral region), it is possible to determine the individual components of the electric current density ($j_{\mathrm{x}}$, $j_{\mathrm{y}}$, $j_{\mathrm{z}}$) with an accuracy of $\sigma =0.90-1.00$ dex, whereas the modulus ($\Vert \mathbf{j}\Vert$) can only be determined with $\sigma =0.75$ dex. In the most complicated case (with multiple spectral regions, a large number of nodes, Tikhonov vertical regularization, and magnetohydrostatic equilibrium), these numbers improve to $\sigma =0.70-0.75$ dex for the individual components and $\sigma =0.5$ dex for the modulus. Moreover, in regions where the magnetic field is above 300 gauss, $\Vert \mathbf{j}\Vert$ can be inferred with an accuracy of $\sigma =0.3$ dex. In general, the $x$ and $y$ components of the electric current density are retrieved slightly better than the $z$ component.

accepted for publication in Astronomy & Astrophysics (A&A): 12 pages, 8 figures, 5 tables

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Cited by in corpus (2)

• Spectropolarimetric Inversion in Four Dimensions with Deep Learning (SPIn4D): I. Overview, Magnetohydrodynamic Modeling, and Stokes Profile Synthesis
• Inference of horizontal velocity fields from the induction equation in the solar atmosphere. I. Analytical and numerical solutions in 2D