Automatic Redshift Determination by Use of Principal Component Analysis. I. Fundamentals

Glazebrook, Karl; Offer, Alison; Deeley, Kathryn

doi:10.1086/305039

Cited by 84 publications

(93 citation statements)

References 13 publications

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“…SpecBS is different from the SDSS official pipeline, since it determines classifications and redshifts via a 2 fit to the spectrum in question with a series of rest-frame star, galaxy, and quasar templates. The basic technique is described by Glazebrook et al (1998) and Bromley et al (1998).…”

Section: The Sloan Digital Sky Surveymentioning

confidence: 99%

Active Galactic Nuclei in the Sloan Digital Sky Survey. I. Sample Selection

Hao¹,

Strauss²,

Tremonti³

et al. 2005

230

206

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We have compiled a large sample of low-redshift active galactic nuclei (AGNs) identified via their emission-line characteristics from the spectroscopic data of the Sloan Digital Sky Survey. Since emission lines are often contaminated by stellar absorption lines , we developed an objective and efficient method of subtracting the stellar continuum from every galaxy spectrum before making emission-line measurements. The distribution of the measured H FWHM values of emission-line galaxies is strongly bimodal, with two populations separated at about 1200 km s À1 . This feature provides a natural separation between narrow-line and broad-line AGNs. The narrowline AGNs are identified using standard emission-line ratio diagnostic diagrams. There are 1317 broad-line and 3074 narrow-line AGNs identified from about 100,000 galaxy spectra selected over 1151 deg 2 . This sample is used in a companion paper to determine the emission-line luminosity function of AGNs.

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Section: The Sloan Digital Sky Surveymentioning

confidence: 99%

Active Galactic Nuclei in the Sloan Digital Sky Survey. I. Sample Selection

Hao¹,

Strauss²,

Tremonti³

et al. 2005

230

206

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“…It has been applied to astronomical spectral datasets for a variety of purposes [e.g. 4,5,6,7,8]. PCA identifies correlated features, such as the Balmer absorption lines, extracting them easily as a single parameter.…”

Section: Star Formation Histories From Galaxy Spectramentioning

confidence: 99%

Quenching of Star Formation

Wild

Budavàri²,

Blaizot³

et al. 2008

AIP Conference Proceedings

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Abstract. In the last decade we have seen an enormous increase in the size and quality of spectroscopic galaxy surveys, both at low and high redshift. New statistical techniques to analyse large portions of galaxy spectra are now finding favour over traditional index based methods. Here we will review a new robust and iterative Principal Component Analysis (PCA) algorithm, which solves several common issues with classic PCA. Application to the 4000Å break region of galaxies in the VIMOS VLT Deep Survey (VVDS) and Sloan Digital Sky Survey (SDSS) gives new high signal-tonoise ratio spectral indices easily interpretable in terms of recent star formation history. In particular, we identify a sample of post-starburst galaxies at z ∼ 0.7 and z ∼ 0.07. We quantify for the first time the importance of post-starburst galaxies, consistent with being descendents of gas-rich major mergers, for building the red sequence. Finally, we present a comparison with new low and high redshift "mock spectroscopic surveys" derived from a Millennium Run semi-analytic model.

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“…This paper proposes and tests a classification approach based on the Principal Component Analysis (PCA), also known as Karhunen-Loève expansion -the underlying principles of the PCA were independently derived by Karhunen (1947) and Loève (1948). The PCA is a non-parametric approach which has been successfully used for a variety of astronomical applications including stellar classification from photometric data (Deeming 1964;Scarfe 1966;Whitney 1983a,b) and from spectra (Storrie-Lombardi et al 1994;Ibata & Irwin 1997;Bailer-Jones et al 1998;Singh et al 1998), galaxy classification from photometric data (Watanabe et al 1985) and from galaxy spectra (Connolly et al 1995a;Connolly et al 1995b;Galaz & de Lapparent 1998;Connolly & Szalay 1999;Ronen et al 1999), and for galaxy redshift measurements (Glazebrook et al 1998); other fields of application are solar flare observations (Teuber et al 1979), asteroid spectra (Britt et al 1992), inter-stellar medium emission lines (Heyer & Schloerb 1997), gamma ray bursts (Bagoly et al 1998), and active galaxies (Mittaz et al 1990;Dultzin-Hacyan & Ruano 1996;Turler & Courvoisier 1998).…”

Section: Introductionmentioning

confidence: 99%

Classification and redshift estimation by principal component analysis

Cabanac

Lapparent

Hickson

2002

A&A

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Abstract. We show that the first 10 eigencomponents of the Karhunen-Loève expansion or Principal Component Analysis (PCA) provide a robust classification scheme for the identification of stars, galaxies and quasi-stellar objects from multi-band photometry. To quantify the efficiency of the method, realistic simulations are performed which match the planned Large Zenith Telescope survey. This survey is expected to provide spectral energy distributions with a resolution R 40 for ∼10 6 galaxies to R ≤ 23 (z ∼ 1), ∼ 10 4 QSOs, and ∼ 10 5 stars. We calculate that for a median signal-to-noise ratio of 6, 98% of stars, 100% of galaxies and 93% of QSOs are correctly classified. These values increase to 100% of stars, 100% of galaxies and 100% of QSOs at a median signal-to-noise ratio of 10. The 10-component PCA also allows measurement of redshifts with an accuracy of σRes. < ∼ 0.05 for galaxies with z < ∼ 0.7, and to σRes. < ∼ 0.2 for QSOs with z > ∼ 2, at a median signal-to-noise ratio of 6. At a median signal-to-noise ratio 20, σRes. < ∼ 0.02 for galaxies with z < ∼ 1 and for QSOs with z > ∼ 2.5 (note that for a median S/N ratio of 20, the bluest/reddest objects will have a signal-to-noise ratio of < ∼ 2 in their reddest/bluest filters). This redshift accuracy is inherent to the R 40 resolution provided by the set of medium-band filters used by the Large Zenith Telescope survey. It provides an accuracy improvement of nearly an order of magnitude over the photometric redshifts obtained from broad-band BV RI photometry.

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Automatic Redshift Determination by Use of Principal Component Analysis. I. Fundamentals

Cited by 84 publications

References 13 publications

Active Galactic Nuclei in the Sloan Digital Sky Survey. I. Sample Selection

Active Galactic Nuclei in the Sloan Digital Sky Survey. I. Sample Selection

Quenching of Star Formation

Classification and redshift estimation by principal component analysis

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