Inversions of artificial time-distance data using mainly Born approximation kernels and the MCD algorithm

Computer Science – Sound

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Scientific paper

Local helioseismology, more specifically time-distance analysis, is a recent development in solar physics that gives us invaluable insight into the upper layers of the Sun. In this poster we show the results of a hare-and-hounds exercise concerning the inversion of time-distance data for perturbations to the sound-speed. We base our analysis on the Born approximation, which is expected to be more accurate than the usual ray-path approximation. We produce artificial time-distance data by solving the forward problem for travel times in the Born approximation. To invert these data, we apply the MCD (Multi-Channel Deconvolution) with Born approximation kernels, and the MCD and LSQR algorithms with ray theory kernels. We will present a detailed comparison between the different inversion results.

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