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Gaia-ESO Survey observations of the young Gamma Velorum cluster led to the discovery of two kinematically-distinct populations, Gamma Vel A and B, respectively, with population B extended over several square degrees in the Vela OB2 association. Using the Gaia DR2 data for a sample of high-probability cluster members, we find that the two populations differ not only kinematically, but are also located at different distances along the line of sight, with the main cluster Gamma Vel A being closer. A combined fit of the two populations yields $varpi_A = 2.895 pm 0.008$ mas and $varpi_B = 2.608 pm 0.017$ mas, with intrinsic dispersions of $0.038 pm 0.011$ mas and $0.091 pm 0.016$ mas, respectively. This translates into distances of $345.4^{+1.0+12.4}_{-1.0-11.5},$ pc and $383.4^{+2.5+15.3}_{-2.5-14.2},$ pc, respectively, showing that Gamma Vel A is closer than Gamma Vel B by $sim$38 pc. We find that the two clusters are nearly coeval, and that Gamma Vel B is expanding. We suggest that Gamma Vel A and B are two independent clusters located along the same line of sight.
Understanding the properties of young open clusters, such as the Initial Mass Function (IMF), star formation history and dynamic evolution, is crucial to obtain reliable theoretical predictions of the mechanisms involved in the star formation process
Context: Lupus is recognised as one of the closest star-forming regions, but the lack of trigonometric parallaxes in the pre-Gaia era hampered many studies on the kinematic properties of this region and led to incomplete censuses of its stellar popul
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Knowledge of the abundance distribution of star forming regions and young clusters is critical to investigate a variety of issues, from triggered star formation and chemical enrichment by nearby supernova explosions to the ability to form planetary s
The combination of precise radial velocities from multi-object spectroscopy and highly accurate proper motions from Gaia DR2 opens up the possibility for detailed 3D kinematic studies of young star forming regions and clusters. Here, we perform such