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Zeeman-Doppler imaging: old problems and new methods

Published online by Cambridge University Press:  01 November 2008

Thorsten A. Carroll ,
Markus Kopf ,
Klaus G. Strassmeier  and
Ilya Ilyin
Thorsten A. Carroll
Affiliation:
Astrophysikalisches Institut Potsdam, An der Sternwarte 16, D-14482 Potsdam, Germany email: tcarroll@aip.de
Markus Kopf
Affiliation:
Astrophysikalisches Institut Potsdam, An der Sternwarte 16, D-14482 Potsdam, Germany email: tcarroll@aip.de
Klaus G. Strassmeier
Affiliation:
Astrophysikalisches Institut Potsdam, An der Sternwarte 16, D-14482 Potsdam, Germany email: tcarroll@aip.de
Ilya Ilyin
Affiliation:
Astrophysikalisches Institut Potsdam, An der Sternwarte 16, D-14482 Potsdam, Germany email: tcarroll@aip.de
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Abstract

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Zeeman-Doppler Imaging (ZDI) is a powerful inversion method to reconstruct stellar magnetic surface fields. The reconstruction process is usually solved by translating the inverse problem into a regularized least-square or optimization problem. In this contribution we will emphasize that ZDI is an inherent non-linear problem and the corresponding regularized optimization is, like many non-linear problems, potentially prone to local minima. We show how this problem will be exacerbated by using an inadequate forward model. To facilitate a more consistent full radiative transfer driven approach to ZDI we describe a two-stage strategy that consist of a principal component analysis (PCA) based line profile reconstruction and a fast approximate polarized radiative transfer method to synthesize local Stokes profiles. Moreover, we introduce a novel statistical inversion method based on artificial neural networks (ANN) which provide a fast calculation of a first guess model and allows to incorporate better physical constraints into the inversion process.

Keywords

Stars: activity – stars: magnetic fields – stars: spots – radiative transfer – methods: data analysis

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