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Main Authors: Korzennik, Sylvain G., Eff-Darwich, Antonio
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2406.10183
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author Korzennik, Sylvain G.
Eff-Darwich, Antonio
author_facet Korzennik, Sylvain G.
Eff-Darwich, Antonio
contents We present a new iterative rotation inversion technique based on the Simultaneous Algebraic Reconstruction Technique developed for image reconstruction. We describe in detail our algorithmic implementation and compare it to the classical inversion techniques like the Regularized Least Squares (RLS) and the Optimally Localized Averages (OLA) methods. In our implementation, we are able to estimate the formal uncertainty on the inferred solution using standard error propagation, and derive the averaging kernels without recourse to any Monte-Carlo simulation. We present the potential of this new technique using simulated rotational frequency splittings. We use noiseless sets that cover the range of observed modes and associate to these artificial splittings observational uncertainties. We also add random noise to present the noise magnification immunity of the method. Since the technique is iterative we also show its potential when using an apriori solution. With the right regularization this new method can outperform our RLS implementation in precision, scope and resolution. Since it results in very different averaging kernels where the solution is poorly constrained, this technique infers different values. Adding such a technique to our compendium of inversion methods will allow us to improve the robustness of our inferences when inverting real observations and better understand where they might be biased and/or unreliable, as we push our techniques to maximize the diagnostic potential of our observations.
format Preprint
id arxiv_https___arxiv_org_abs_2406_10183
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A SART-Based Iterative Inversion Methodology to Infer the Solar Rotation Rate from Global Helioseismic Data
Korzennik, Sylvain G.
Eff-Darwich, Antonio
Solar and Stellar Astrophysics
Instrumentation and Methods for Astrophysics
We present a new iterative rotation inversion technique based on the Simultaneous Algebraic Reconstruction Technique developed for image reconstruction. We describe in detail our algorithmic implementation and compare it to the classical inversion techniques like the Regularized Least Squares (RLS) and the Optimally Localized Averages (OLA) methods. In our implementation, we are able to estimate the formal uncertainty on the inferred solution using standard error propagation, and derive the averaging kernels without recourse to any Monte-Carlo simulation. We present the potential of this new technique using simulated rotational frequency splittings. We use noiseless sets that cover the range of observed modes and associate to these artificial splittings observational uncertainties. We also add random noise to present the noise magnification immunity of the method. Since the technique is iterative we also show its potential when using an apriori solution. With the right regularization this new method can outperform our RLS implementation in precision, scope and resolution. Since it results in very different averaging kernels where the solution is poorly constrained, this technique infers different values. Adding such a technique to our compendium of inversion methods will allow us to improve the robustness of our inferences when inverting real observations and better understand where they might be biased and/or unreliable, as we push our techniques to maximize the diagnostic potential of our observations.
title A SART-Based Iterative Inversion Methodology to Infer the Solar Rotation Rate from Global Helioseismic Data
topic Solar and Stellar Astrophysics
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2406.10183