A modified R1 X R1 method for helioseismic rotation inversions
classification
🌌 astro-ph
keywords
methodinversionssolaaveragingefficienthelioseismicrotationalgorithm
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We present an efficient method for two dimensional inversions for the solar rotation rate using the Subtractive Optimally Localized Averages (SOLA) method and a modification of the R1 X R1 technique proposed by Sekii (1993). The SOLA method is based on explicit construction of averaging kernels similar to the Backus-Gilbert method. The versatility and reliability of the SOLA method in reproducing a target form for the averaging kernel, in combination with the idea of the R1 X R1 decomposition, results in a computationally very efficient inversion algorithm. This is particularly important for full 2-D inversions of helioseismic data in which the number of modes runs into at least tens of thousands.
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