University of Hertfordshire

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From the same journal

By the same authors

VIRAC: The VVV Infrared Astrometric Catalogue

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Original languageEnglish
Number of pages24
Pages (from-to)1826-1849
JournalMonthly Notices of the Royal Astronomical Society
Journal publication date21 Feb 2018
Volume474
Issue2
Early online date7 Nov 2017
DOIs
Publication statusPublished - 21 Feb 2018

Abstract

We present VIRAC version 1, a near-infrared proper motion and parallax catalogue of the VISTA Variables in the Via Lactea (VVV) survey for 312 587 642 unique sources averaged across all overlapping pawprint and tile images covering 560 deg 2 of the bulge of the MilkyWay and southern disc. The catalogue includes 119 million high-quality proper motion measurements, of which 47 million have statistical uncertainties below 1 mas yr -1. In the 11 < K s < 14 magnitude range, the high-quality motions have a median uncertainty of 0.67 mas yr -1. The catalogue also includes 6935 sources with quality-controlled 5s parallaxes with a median uncertainty of 1.1 mas. The parallaxes show reasonable agreement with the Tycho- Gaia Astrometric Solution, though caution is advised for data with modest significance. The SQL data base housing the data is made available via the web. We give example applications for studies of Galactic structure, nearby objects (low-mass stars and brown dwarfs, subdwarfs, white dwarfs) and kinematic distance measurements of young stellar objects. Nearby objects discovered include LTT 7251 B, an L7 benchmark companion to a G dwarf with over 20 published elemental abundances, a bright L subdwarf, VVV 1256-6202, with extremely blue colours and nine new members of the 25 pc sample. We also demonstrate why this catalogue remains useful in the era of Gaia. Future versions will be based on profile fitting photometry, use the Gaia absolute reference frame and incorporate the longer time baseline of the VVV extended survey.

Notes

© 2017 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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