TL;DR
This paper presents a Julia code for accurately computing helioseismic sensitivity kernels in spherical geometry, including line-of-sight projection effects, to improve the analysis of solar interior flows.
Contribution
The paper introduces a novel Julia implementation for evaluating spherical helioseismic sensitivity kernels that incorporate line-of-sight projection effects efficiently.
Findings
Projection effects significantly alter kernel shapes.
Including projection does not increase computational time.
Kernels for rotated point pairs can be computed via linear transformation.
Abstract
Context: Helioseismic analysis of large-scale flows and structural inhomogeneities in the Sun requires the computation of sensitivity kernels that account for the spherical geometry of the Sun, as well as systematic effects such as line-of-sight projection. Aim: I aim to develop a code to evaluate helioseismic sensitivity kernels for flows using line-of-sight projected measurements. Methods: I decomposed the velocity field in a basis of vector spherical harmonics and computed the kernel components corresponding to the coefficients of velocity in this basis. The kernels thus computed are radial functions that set up a 1.5D inverse problem to infer the flow from surface measurements. I demonstrate that using the angular momentum addition formalism lets us express the angular dependence of the kernels as bipolar spherical harmonics, which may be evaluated accurately and efficiently.…
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