Compression and Classification Methods for Galaxy Spectra in Large Redshift Surveys
نویسنده
چکیده
Methods for compression and classification of galaxy spectra, which are useful for large galaxy redshift surveys (such as the SDSS, 2dF, 6dF and VIRMOS), are reviewed. In particular, we describe and contrast three methods: (i) Principal Component Analysis, (ii) Information Bottleneck, and (iii) Fisher Matrix. We show applications to 2dF galaxy spectra and to mock semi-analytic spectra, and we discuss how these methods can be used to study physical processes of galaxy formation, clustering and galaxy biasing in the new large redshift surveys.
منابع مشابه
Recovering physical parameters from galaxy spectra using MOPED
We derive physical parameters of galaxies from their observed spectrum, using MOPED, the optimized data compression algorithm of Heavens, Jimenez & Lahav (2000). Here we concentrate on parametrising galaxy properties, and apply the method to the NGC galaxies in Kennicutt’s spectral atlas. We focus on deriving the star formation history, metallicity and dust content of galaxies. The method is ve...
متن کاملThe Deep2 Galaxy Redshift Survey: Spectral Classification of Galaxies
We present a Principal Component Analysis (PCA)-based spectral classification, η, for the first 5600 galaxies observed in the DEEP2 Redshift Survey. This parameter provides a very pronounced separation between absorption and emission dominated galaxy spectra – corresponding to passively evolving and actively star-forming galaxies in the survey respectively. In addition it is shown that despite ...
متن کامل0 Evidence for Inconsistencies in Galaxy Luminosity Functions Defined by Spectral Type
Galaxy morphological and spectroscopic types should be nearly independent of apparent magnitude in a local, magnitude-limited sample. Recent luminosity function surveys based on morphological classification of galaxies are substantially more successful at passing this test than surveys based on spectroscopic classifications. Among spectroscopic classifiers, those defined by small aperture fiber...
متن کاملAn Artificial Neural Network Approach to Classification of Galaxy Spectra
We present a method for automated classification of galaxies with low signal-to-noise (S/N) spectra typical of redshift surveys. We develop spectral simulations based on the parameters for the 2dF Galaxy Redshift Survey, and with these simulations we investigate the technique of Principal Component Analysis when applied specifically to spectra of low S/N. We relate the objective principal compo...
متن کاملExtracting Cosmological Information from Galaxy Spectra and Observations of High-redshift Objects
I review the statistical techniques needed to extract information about physical parameters of galaxies from their observed spectra. This is important given the sheer size of the next generation of large galaxy redshift surveys. Going to the opposite extreme I review what we can learn about the nature of the primordial density field from observations of high–redshift objects. 1. Extracting cosm...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2000