EDP Sciences
Free Access
Volume 378, Number 1, October IV 2001
Page(s) 316 - 326
Section Instruments, observational techniques and data processing
DOI https://doi.org/10.1051/0004-6361:20011167
Published online 15 October 2001

A&A 378, 316-326 (2001)
DOI: 10.1051/0004-6361:20011167

The inversion of Stokes profiles with artificial neural networks

T. A. Carroll and J. Staude

Astrophysikalisches Institut Potsdam, Telegrafenberg, Sonnenobservatorium Einsteinturm, 14473 Potsdam, Germany

(Received 2 July 2001 / Accepted 10 August 2001 )

We investigate the application of artificial neural networks (ANNs) for the interpretation of Stokes profiles. We have employed ANNs to approximate the nonlinear inverse mapping between the Stokes profiles and some of the underlying atmospheric parameters. This approximate model is used in the following to carry out a fast non-iterative inversion of synthetic Stokes profiles. We have used synthetic Stokes profiles of the photospheric infrared line Fe I $\lambda$15648 to demonstrate that the ANNs are capable to yield accurate single valued estimates of the complete magnetic field vector, line-of-sight (LOS) velocity, microturbulence, macroturbulence and the filling factor with exceptional speed. For a stratified atmosphere we also demonstrate that these single valued parameters do represent very good averaged values of the input stratification. To retrieve some of the temperature information encoded in the Stokes profiles we modeled a neural network classifier on the basis of several semi-empirical model atmospheres (i.e. temperature and pressure stratification). With this classifier we are able to determine the probability that a given Stokes profile has its origin from a particular temperature stratification of a semi-empirical model.

Key words: line: formation -- line: profiles -- Sun: photosphere -- Sun: magnetic fields -- method: data analysis

Offprint request: T. A. Carroll, tcarroll@aip.de

© ESO 2001

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