Machine Learning for Stellar Magnetic Field Determination

In this work we present the results for the automatic determination of the mean longitudinal magnetic field in polarized stellar spectra through the analysis of spectropolarimetric observations. In order to determine this important parameter, we first developed a synthetic database encompassing a se...

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Published inInternational journal of computational intelligence systems Vol. 11; no. 1; pp. 608 - 615
Main Authors Córdova Barbosa, J. P., Navarro Jiménez, S. G., Ramírez Vélez, J. C.
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 2018
Springer
Subjects
Artificial Neural Networks
Machine Learning
Parameter Determination
Research Article
Stellar: Magnetic Fields
Artificial Neural Networks
Machine Learning
Stellar: Magnetic Fields
Parameter Determination
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Abstract In this work we present the results for the automatic determination of the mean longitudinal magnetic field in polarized stellar spectra through the analysis of spectropolarimetric observations. In order to determine this important parameter, we first developed a synthetic database encompassing a set of different stellar spectra, each one defined by a set of free parameters. Then, we used supervised learning for artificial neural networks, a machine learning approach, to achieve our goal.
AbstractList Abstract In this work we present the results for the automatic determination of the mean longitudinal magnetic field in polarized stellar spectra through the analysis of spectropolarimetric observations. In order to determine this important parameter, we first developed a synthetic database encompassing a set of different stellar spectra, each one defined by a set of free parameters. Then, we used supervised learning for artificial neural networks, a machine learning approach, to achieve our goal.
In this work we present the results for the automatic determination of the mean longitudinal magnetic field in polarized stellar spectra through the analysis of spectropolarimetric observations. In order to determine this important parameter, we first developed a synthetic database encompassing a set of different stellar spectra, each one defined by a set of free parameters. Then, we used supervised learning for artificial neural networks, a machine learning approach, to achieve our goal.
Author Córdova Barbosa, J. P.
Navarro Jiménez, S. G.
Ramírez Vélez, J. C.
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Machine Learning
Stellar: Magnetic Fields
Parameter Determination
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SubjectTerms Artificial Neural Networks
Machine Learning
Parameter Determination
Research Article
Stellar: Magnetic Fields
Title Machine Learning for Stellar Magnetic Field Determination
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