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Time-varying phenomena are one of the most substantial sources ofastrophysical information and their study has led to many fundamentaldiscoveries in modern astronomy. We have developed an automated tool to searchand analyze variable sources in the near infrared $\rm K_{s}$-band, using thedata from the Vista Variables in the V\'ia L\'actea (VVV) ESO Public LargeSurvey. This process relies on the characterization of variable sources usingdifferent variability indices, calculated from time series generated with PointSpread Function photometry of sources under analysis. In particular, we usedtwo main indices: the total amplitude $\rm \Delta K_s$ and the eta index,$\eta$, to identify variable sources. Once variable objects are identified,periods are determined with Generalized Lomb-Scargle periodograms, and theInformation Potential Metric. Variability classes are assigned according to acompromise between comparisons with VVV Templates and the period of thevariability. The automated tool is applied on VVV tiles d001 and d002 and ledto discovery of 200 variable sources. We detected 70 irregular variable sourcesand 130 periodic ones. In addition nine open cluster candidates projected inthe region are analyzed, the infrared variable candidates found around theseclusters are further scrutinized by cross-matching their locations againstemission star candidates from VPHAS+ survey $\rm H_{\alpha}$ color cuts.

astrophysical journal/the astrophysical journal

An Automated tool to detect variable sources in the Vista Variables in  the V\'{\i}a L\'actea Survey. The VVV Variables (V$^{4}$) catalog of tiles  d001 and d002