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Title: DETECTING VARIABILITY IN MASSIVE ASTRONOMICAL TIME-SERIES DATA. II. VARIABLE CANDIDATES IN THE NORTHERN SKY VARIABILITY SURVEY

Journal Article · · Astronomical Journal (New York, N.Y. Online)
 [1]; ; ;  [2];  [3]
  1. Department of Astronomy, The University of Michigan, 500 Church Street, Ann Arbor, MI 48109 (United States)
  2. Department of Astronomy, Yonsei University, Seoul 120-749 (Korea, Republic of)
  3. Department of Astronomy and University Observatory, Yonsei University, Seoul 120-749 (Korea, Republic of)

We present variability analysis of data from the Northern Sky Variability Survey (NSVS). Using the clustering method, which defines variable candidates as outliers from large clusters, we cluster 16,189,040 light curves having data points at more than 15 epochs as variable and non-variable candidates in 638 NSVS fields. Variable candidates are selected depending on how strongly they are separated from the largest cluster and how rarely they are grouped together in eight-dimensional space spanned by variability indices. All NSVS light curves are also cross-correlated with IRAS, AKARI, Two Micron All Sky Survey, Sloan Digital Sky Survey (SDSS), and GALEX objects, as well as known objects in the SIMBAD database. The variability analysis and cross-correlation results are provided in a public online database, which can be used to select interesting objects for further investigation. Adopting conservative selection criteria for variable candidates, we find about 1.8 million light curves as possible variable candidates in the NSVS data, corresponding to about 10% of our entire NSVS sample. Multi-wavelength colors help us find specific types of variability among the variable candidates. Moreover, we also use morphological classification from other surveys such as SDSS to suppress spurious cases caused by blending objects or extended sources due to the low angular resolution of the NSVS.

OSTI ID:
22034687
Journal Information:
Astronomical Journal (New York, N.Y. Online), Vol. 143, Issue 3; Other Information: Country of input: International Atomic Energy Agency (IAEA); ISSN 1538-3881
Country of Publication:
United States
Language:
English

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