Quasi-stellar object selection algorithm using time variability and machine learning: Selection of 1620 quasi-stellar object candidates from MACHO Large Magellanic Cloud database

Astrophysical Journal

Volumn 735, Issue 2, 2011, Pages

  Kim, Dae Won ^a,b,c   Protopapas, Pavlos ^a,c   Byun, Yong Ik ^b   Alcock, Charles ^a   Khardon, Roni ^d   Trichas, Markos ^a  

^a HARVARD SMITHSONIAN CENTER FOR ASTROPHYSICS   (United States)

^b Yonsei University   (South Korea)

^c HARVARD UNIVERSITY   (United States)

^d Tufts University   (United States)

Author keywords

Magellanic Clouds; methods: data analysis; quasars: general

Indexed keywords

EID: 79959918266     PISSN: 0004637X     EISSN: 15384357     Source Type: Journal    
DOI: 10.1088/0004-637X/735/2/68     Document Type: Article

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