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Estimation of Alpha-Element Abundance Ratios Based on Gaussian Process Regression

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Abstract:

In this paper, we present a method to estimate the [α/Fe ]using the spectra from ninth data release of Sloan Digital Sky Survey (SDSS). We first use principal component analysis (PCA) to reduce the dimension of the spectra, and then use Gaussian process regression (GPR) to estimate the [α/Fe ]ratios. The results show that GPR is accurate and efficient in estimating the [α/Fe]ratios. Further analysis shows that using PCA can improve the estimation accuracy of GPR.

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Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

1685-1688

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.1685

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Online since:

March 2014

Authors:

Yu De Bu, Jing Chang Pan*, Jie Wang

Keywords:

Alpha-Element Abundance, Gaussian Process Regression, PCA

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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