The VMC survey

Context. The near-infrared YJK s Visual and Infrared Survey Telescope for Astronomy (VISTA) survey of the Magellanic Clouds (VMC) is complete, along with data from additional programmes contributing to the enhancement of its quality over the original footprints. Aims. This work presents the final data release of the VMC survey, which includes additional observations and provides an overview of the scientific results. The overall data quality has been revised and reprocessed standard data products that have previously appeared in earlier data releases are made available together with new data products. These include the individual stellar proper motions, reddening towards red clump stars, and source classifications. Several data products, such as the parameters of some variable stars and of background galaxies, from the VMC publications have been associated with a data release for the first time. Methods. The data were processed using the VISTA Data Flow System and additional products (e.g. catalogues with point-spread-function photometry and tables with stellar proper motions) were obtained with software developed by the survey team. Results. This release supersedes all previous data releases of the VMC survey for the combined (deep-stacked) data products, whilst providing additional (complementary) images and catalogues of single observations per filter. Overall, it includes about 64 million detections, split nearly evenly between sources with stellar or galaxy profiles. Conclusions. The VMC survey provides a homogeneous data set resulting from deep and multi-epoch YJK s -band imaging observations of the Large and Small Clouds, the Bridge, and two fields in the Stream. The VMC data represent a valuable counterpart for sources detected at other wavelengths for both stars and background galaxies.

Authors

Institutions

Publication Details

Journal
Astronomy and Astrophysics
Published
2025-06-11
DOI
https://doi.org/10.1051/0004-6361/202554254
Citations
2
Primary Topic
Astronomy and Astrophysical Research
Type
article
Field-Weighted Citation Impact
2.38

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The VMC survey

F. Cusano, Luca Cioni, Richard de Grijs, M. Marconi et al.
2 citations
Astronomy and Astrophysics
Astronomy and Astrophysical Research
2.38
article

The VMC survey

F. Cusano, Luca Cioni, Richard de Grijs, M. Marconi, C. M. Pennock, M. A. Read, Jessica E. M. Craig, R. G. Mann, E. Sutorius, Abinaya O. Omkumar, G. Clementini, N. J. G. Cross, Mark Holliman, S. Subramanian, Jacco Th. van Loon, Florian Niederhofer, V. Ripepi, L. Girardi, M. A. T. Groenewegen, R. Molinaro, S. Zaggia, F. Dresbach, V. D. Ivanov, K. Bekki, Robert Blake, C. Maitra, T. Sicignano, J. M. Oliveira, Jonathan Irwin, B. L. Tatton, M. Irwin, Sreepriya Vijayasree
article en
2 citations

Abstract

Context. The near-infrared YJK s Visual and Infrared Survey Telescope for Astronomy (VISTA) survey of the Magellanic Clouds (VMC) is complete, along with data from additional programmes contributing to the enhancement of its quality over the original footprints. Aims. This work presents the final data release of the VMC survey, which includes additional observations and provides an overview of the scientific results. The overall data quality has been revised and reprocessed standard data products that have previously appeared in earlier data releases are made available together with new data products. These include the individual stellar proper motions, reddening towards red clump stars, and source classifications. Several data products, such as the parameters of some variable stars and of background galaxies, from the VMC publications have been associated with a data release for the first time. Methods. The data were processed using the VISTA Data Flow System and additional products (e.g. catalogues with point-spread-function photometry and tables with stellar proper motions) were obtained with software developed by the survey team. Results. This release supersedes all previous data releases of the VMC survey for the combined (deep-stacked) data products, whilst providing additional (complementary) images and catalogues of single observations per filter. Overall, it includes about 64 million detections, split nearly evenly between sources with stellar or galaxy profiles. Conclusions. The VMC survey provides a homogeneous data set resulting from deep and multi-epoch YJK s -band imaging observations of the Large and Small Clouds, the Bridge, and two fields in the Stream. The VMC data represent a valuable counterpart for sources detected at other wavelengths for both stars and background galaxies.

Astronomy and AstrophysicsVol. 699
European Southern Observatory (DE), Indian Institute of Astrophysics (IN), University of Potsdam (DE), The University of Western Australia (AU), University of Cambridge (GB), Royal Observatory of Belgium (BE), Leibniz Institute for Astrophysics Potsdam (DE), Astronomical Observatory of Capodimonte (IT), Max Planck Institute for Extraterrestrial Physics (DE), Royal Observatory (GB), Istituto Nazionale di Fisica Nucleare, Sezione di Napoli (IT), Scuola Superiore Meridionale (IT), International Space Science Institute - Beijing (CN), Osservatorio Astronomico di Padova (IT), International Centre for Radio Astronomy Research (AU), Osservatorio di Astrofisica e Scienza dello Spazio, UK Astronomy Technology Centre (GB), Keele University (GB), National Institute for Astrophysics (IT), Macquarie University (AU)
Science and Technology Facilities Council
Openalex Percentile: Top 12%
Astronomy and Astrophysical Research
2.38
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.