outlier detection algorithm for SDSS galaxies : J/MNRAS/465/4530

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Authors : Baron D. orcid , Poznanski D. (hide) , Poznanski D. et..al

VizieR DOI : 10.26093/cds/vizier.74654530
Bibcode : 2017MNRAS.465.4530B (ADS) (Simbad) (Objects)
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CDS Keywords : Galaxy catalogs; Redshifts
UAT : Galaxies, Catalogs, Redshifted

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Inserted into VizieR : 12-Sep-2019
Last modification : 16-Aug-2024

The weirdest SDSS galaxies results from an outlier detection algorithm. (2017)

Keywords : methods data analysis - methods: statistical - galaxies: general - galaxies: peculiar

Abstract:How can we discover objects we did not know existed within the large data sets that now abound in astronomy? We present an outlier detection algorithm that we developed, based on an unsupervised Random Forest. We test the algorithm on more than two million galaxy spectra from the Sloan Digital Sky Survey and examine the 400 galaxies with the highest outlier score. We find objects which have extreme emission line ratios and abnormally strong absorption lines, objects with unusual continua, including extremely reddened galaxies. We find galaxy-galaxy gravitational lenses, double-peaked emission line galaxies and close galaxy pairs. We find galaxies with high ionization lines, galaxies that host supernovae and galaxies with unusual gas ...(more)
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We have introduced an outlier detection algorithm that is based on an unsupervised implementation of RF. By construction, the algorithm learns the most important features of the data and their interconnections; it is completely general and can be applied to imaging data, time series and other spectroscopic objects as well. Out of 2355926 galaxies that compose the input sample, we chose 400 galaxies with the highest weirdness score. We find objects with unusual emission line ratios, and complex velocity structures, extremely red objects, objects with extremely strong absorption lines (i.e. sodium and H{alpha}), galaxies which host supernovae, or have rare emission lines.

  • V/147 : The SDSS Photometric Catalogue, Release 12 (Alam+, 2015)

                


                

                    

                


                

                    

                


                

                    
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