404 research outputs found
Classification of Stellar Spectra with LLE
We investigate the use of dimensionality reduction techniques for the
classification of stellar spectra selected from the SDSS. Using local linear
embedding (LLE), a technique that preserves the local (and possibly non-linear)
structure within high dimensional data sets, we show that the majority of
stellar spectra can be represented as a one dimensional sequence within a three
dimensional space. The position along this sequence is highly correlated with
spectral temperature. Deviations from this "stellar locus" are indicative of
spectra with strong emission lines (including misclassified galaxies) or broad
absorption lines (e.g. Carbon stars). Based on this analysis, we propose a
hierarchical classification scheme using LLE that progressively identifies and
classifies stellar spectra in a manner that requires no feature extraction and
that can reproduce the classic MK classifications to an accuracy of one type.Comment: 15 pages, 13 figures; accepted for publication in The Astronomical
Journa
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