VISIONS is an ESO public survey of five nearby (d < 500 pc) star-forming molecular cloud complexes that are canonically associated with the constellations of Chamaeleon, Corona Australis, Lupus, Ophiuchus, and Orion. The survey was carried out with the Visible and Infrared Survey Telescope for Astronomy (VISTA), using the VISTA Infrared Camera (VIRCAM), and collects data in the near-infrared passbands J (1.25 µm), H (1.65 µm), and K S (2.15 µm). With a total on-sky exposure time of 49.4 h VISIONS covers an area of 650 deg 2 , it is designed to build an infrared legacy archive with a structure and content similar to the Two Micron All Sky Survey (2MASS) for the screened star-forming regions. Taking place between April 2017 and March 2022, the observations yielded approximately 1.15 million images, which comprise 19 TB of raw data. The observations undertaken within the survey are grouped into three different subsurveys. First, the wide subsurvey comprises shallow, large-scale observations and it has revisited the star-forming complexes six times over the course of its execution. Second, the deep subsurvey of dedicated high-sensitivity observations has collected data on areas with the largest amounts of dust extinction. Third, the control subsurvey includes observations of areas of low-to-negligible dust extinction. Using this strategy, the VISIONS observation program offers multi-epoch position measurements, with the ability to access deeply embedded objects, and it provides a baseline for statistical comparisons and sample completeness -all at the same time. In particular, VISIONS is designed to measure the proper motions of point sources, with a precision of 1 mas yr −1 or better, when complemented with data from the VISTA Hemisphere Survey (VHS). In this way, VISIONS can provide proper motions of complete ensembles of embedded and low-mass objects, including sources inaccessible to the optical ESA Gaia mission. VISIONS will enable the community to address a variety of research topics from a more informed perspective, including the 3D distribution and motion of embedded stars and the nearby interstellar medium, the identification and characterization of young stellar objects, the formation and evolution of embedded stellar clusters and their initial mass function, as well as the characteristics of interstellar dust and the reddening law.
We present a new clustering method, significance mode analysis (SigMA), for extracting co-spatial and co-moving stellar populations from large-scale surveys such as ESA Gaia. The method studies the topological properties of the density field in the multidimensional phase space. We validated SigMA on simulated clusters and find that it outperforms competing methods, especially in cases where many clusters are closely spaced. We applied the new method to Gaia DR3 data of the closest OB association to Earth, Scorpio-Centaurus (Sco-Cen), and find more than 13 000 co-moving young objects, about 19% of which have a substellar mass. SigMA finds 37 co-moving clusters in Sco-Cen. These clusters are independently validated by their narrow Hertzsprung-Russell diagram sequences and, to a certain extent, by their association with massive stars too bright for Gaia, and are hence unknown to SigMA. We compared our results with similar recent work and find that the SigMA algorithm recovers richer populations, is able to distinguish clusters with velocity differences down to about 0.5 km s−1, and reaches cluster volume densities as low as 0.01 sources pc−3. The 3D distribution of these 37 coeval clusters implies a larger extent and volume for the Sco-Cen OB association than typically assumed in the literature. Additionally, we find the association more actively star-forming and dynamically complex than previously thought. We confirm that the star-forming molecular clouds in the Sco-Cen region, namely, Ophiuchus, L134/L183, Pipe Nebula, Corona Australis, Lupus, and Chamaeleon, are part of the Sco-Cen association. The application of SigMA to Sco-Cen demonstrates that advanced machine learning tools applied to the superb Gaia data allows an accurate census of the young populations to be constructed, which in turn allows us to quantify their dynamics and recreate the recent star formation history of the local Milky Way.
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