Chemical evolution and galactic and extragalactic stellar populations, by means of...
Searching for peculiar features in the gas around young stellar clusters
Searching for young stellar groups with machine-learning methods
Grant number: | 17/19458-8 |
Support Opportunities: | Regular Research Grants |
Start date: | February 01, 2018 |
End date: | January 31, 2020 |
Field of knowledge: | Physical Sciences and Mathematics - Astronomy - Stellar Astrophysics |
Principal Investigator: | Annibal Hetem Junior |
Grantee: | Annibal Hetem Junior |
Host Institution: | Centro de Engenharia, Modelagem e Ciências Sociais Aplicadas (CECS). Universidade Federal do ABC (UFABC). Ministério da Educação (Brasil). Santo André , SP, Brazil |
Abstract
We intend to make an analysis of a large sample of clusters of young stars in order to investigate the inherent properties of clustering and dynamic evolution of stellar components. The statistical parameter Q measured for the clusters, and its correlations with the estimated fractal dimension for the projected near clouds. In previous works, we measured the parameter Q for a set of 25 clusters and the results were correlated with other properties of the spatial distributions determined through the King profile and show that almost half of these groups have a relation with the fractal dimension of their parental cloud. There are also indications of the presence of substructures similar to those observed in the surrounding clouds. However, other clusters have a radial distribution that does not coincide with the structure of the clouds. These properties may lead to conclusions about the initial conditions of clusters formation (cold collapse or hot collapse), initial evolution (bound or not) and its expected galactic dynamic evolution (crossing time). These studies may give us information about the history of the influence of the Galaxy on clusters and how they were affected by their passage through their structures. In addition, we intend to study the application of new mathematical and numerical techniques with potentiality for use in models of filamentary structures. (AU)
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