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2018ApJ...864...11M - Astrophys. J., 864, 11-11 (2018/September-1)

An automated tool to detect variable sources in the VISTA Variables in the Via Lactea Survey: the VVV Variables (V4) catalog of tiles d001 and d002.

MEDINA N., BORISSOVA J., BAYO A., KURTEV R., NAVARRO MOLINA C., KUHN M., KUMAR N., LUCAS P.W., CATELAN M., MINNITI D. and SMITH L.C.

Abstract (from CDS):

Time-varying phenomena are one of the most substantial sources of astrophysical information, and their study has led to many fundamental discoveries in modern astronomy. We have developed an automated tool to search for and analyze variable sources in the near-infrared Ks band using the data from the VISTA Variables in the Via Lactea (VVV) ESO Public Large Survey. This process relies on the characterization of variable sources using different variability indices calculated from time series generated with point-spread function (PSF) photometry of sources under analysis. In particular, we used two main indices, the total amplitude ΔKs and the eta index η, to identify variable sources. Once the variable objects are identified, periods are determined with generalized Lomb-Scargle periodograms and the information potential metric. Variability classes are assigned according to a compromise between comparisons with VVV templates and the period of the variability. The automated tool is applied on VVV tiles d001 and d002 and led to the discovery of 200 variable sources. We detected 70 irregular variable sources and 130 periodic ones. In addition, nine open-cluster candidates projected in the region are analyzed, and the infrared variable candidates found around these clusters are further scrutinized by cross-matching their locations against emission star candidates from VPHAS+ survey Hα color cuts.

Abstract Copyright: © 2018. The American Astronomical Society. All rights reserved.

Journal keyword(s): catalogs - open clusters and associations: general - stars: pre-main sequence - techniques: photometric

VizieR on-line data: <Available at CDS (J/ApJ/864/11): table3.dat table4.dat table5.dat>

Nomenclature: Table 4: [MBB2018] CL00N CNN (Nos CL005 C1-CL005 C10, CL007 C1-CL007 C6, CL008 C1-CL008 C2), [MBB2018] LS0NN CNN (Nos LS001 C1-LS001 C9, LS002 C1-LS002 C22, LS003 C1-LS003 C12, LS009 C1-LS009 C9, LS015 C1-LS015 C3). Table 5: [MBB2018] d001-NN (Nos 1-93), [MBB2018] d002-NNN (Nos 1-108).

Simbad objects: 288

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