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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: [email protected]
Markus Kopf
Affiliation:
Astrophysikalisches Institut Potsdam, An der Sternwarte 16, D-14482 Potsdam, Germany email: [email protected]
Klaus G. Strassmeier
Affiliation:
Astrophysikalisches Institut Potsdam, An der Sternwarte 16, D-14482 Potsdam, Germany email: [email protected]
Ilya Ilyin
Affiliation:
Astrophysikalisches Institut Potsdam, An der Sternwarte 16, D-14482 Potsdam, Germany email: [email protected]
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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
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 4 , Symposium S259: Cosmic Magnetic Fields: From Planets, to Stars and Galaxies , November 2008 , pp. 633 - 644
Copyright
Copyright © International Astronomical Union 2009

References

Berdyugina, S. V. 2007, Mem. Soc. Astr. It. 78, 242Google Scholar
Berdyugina, S. V., Jankov, S., Ilyin, I., Tuominen, I., & Fekel, F. C. 1998, A&A 334, 863Google Scholar
Bishop, C. M., 1995, Neural Networks for Pattern Recognition, Oxford University PressCrossRefGoogle Scholar
Brown, S. F., Donati, J.-F., Rees, D. E., & Semel, M. 1991, A&A 250, 463Google Scholar
Carroll, T. A., Kopf, M., Ilyin, I., & Strassmeier, K. G. 2009, A&A, in prep.Google Scholar
Carroll, T. A. & Kopf, M. 2008, A&A 481, L37Google Scholar
Carroll, T. A., Kopf, M., & Strassmeier, K. G. 2008, A&A 488, 781Google Scholar
Carroll, T. A., Kopf, M., Ilyin, I., & Strassmeier, K. G. 2007, AN 328, 1043Google Scholar
Carroll, T. A. & Staude, J. 2001, A&A 378, 316Google Scholar
Donati, J.-F., Jardine, M. M., Gregory, S. G., Petit, P., Bouvier, J., Dougados, C., Mnard, F., Cameron, A. C., Harries, T. J., Jeffers, S. V., & Paletou, F. 2007, MNRAS 380, 1297CrossRefGoogle Scholar
Donati, J.-F., Forveille, T., Cameron, A. C., Barnes, J. R., Delfosse, X., Jardine, M. M., & Valenti, J. A. 2006, Science 311, 633CrossRefGoogle Scholar
Donati, J.-F. 1999, MNRAS 302, 457CrossRefGoogle Scholar
Donati, J.-F., Semel, M., Carter, B. D., Rees, D. E., & Collier Cameron, A. 1997, MNRAS 291, 658CrossRefGoogle Scholar
Donati, J.-F., Semel, M., Rees, D. E., Taylor, K., & Robinson, R. D. 1990, A&A 232, L1Google Scholar
Elstner, D. & Korhonen, H. 2005, AN 326, 278Google Scholar
Engl, H. W., Hanke, M., & Neubauer, A. 1996, Regularization of Inverse Problems, Kluwer Academic Publishers Group, Dordrecht, The NetherlandsCrossRefGoogle Scholar
Hussain, G. A. J., van Ballegooijen, A. A., Jardine, M., & Collier Cameron, A. 2002, ApJ 575, 1078CrossRefGoogle Scholar
Kochukhov, O., Bagnulo, S., Wade, G. A., Sangalli, L., Piskunov, N., Landstreet, J. D., Petit, P., & Sigut, T. A. A. 2004, A&A 414, 613Google Scholar
Landi Deglinnocenti, E. & Landi Deglinnocenti, M. 1985, SP 97, 239Google Scholar
Martínez González, M. J., Asensio Ramos, A., Carroll, T. A., Kopf, M., Ramírez Vélez, J. C., & Semel, M. 2008, A&A 486, 637Google Scholar
Petit, P., Dintrans, B., Solanki, S. K., Donati, J.-F., Aurire, M., Lignires, F., Morin, J., Paletou, F., Ramirez Velez, J., Catala, C., & Fares, R. et al. 2008, MNRAS, 388, 80CrossRefGoogle Scholar
Piskunov, N. & Kochukhov, O. 2002, A&A 381, 736Google Scholar
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. 1992, Numerical Recipes, Cambridge: University Press, 2nd ed.Google Scholar
Rees, D. E., Durrant, C. J., & Murphy, G. A. 1989, ApJ 339, 1093CrossRefGoogle Scholar
Semel, M. 1989, A&A 225, 456Google Scholar
Strassmeier, K. G., Woche, M., Andersen, M., & Ilyin, I. 2007, AN 328, 627Google Scholar
Strassmeier, K. G., Woche, M., Ilyin, I., Popow, E., Bauer, S.-M., Dionies, F., Fechner, T., Weber, M., Hofmann, A., Storm, J., Materne, R., Bittner, W., Bartus, J., Granzer, T., Denker, C., Carroll, T., Kopf, M., DiVarano, I., Beckert, E., Lesser, M. et al. 2008, Ground-based and Airborne Instrumentation for Astronomy, Proc. of the SPIE, Vol. 7014, p. 70140NCrossRefGoogle Scholar
Stenflo, J. O. 1994, Solar Magnetic Fields – Polarized Radiation Diagnostics, Astrophysics and Space Science Library, 189, Dordrecht, Boston: Kluwer Academic PublishersCrossRefGoogle Scholar