Statistics – Applications
Scientific paper
Nov 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010phdt........90p&link_type=abstract
ProQuest Dissertations And Theses; Thesis (Ph.D.)--University of Cincinnati, 2010.; Publication Number: AAT3419987; ISBN: 978112
Statistics
Applications
Scientific paper
Stellar clusters are laboratories for stellar evolution. Their stellar content have an uniform age and chemical composition, but span a large mass interval. The majority of stars are born in clusters and end up in the general field population. An accurate characterization of stellar clusters could be used to built better models, from stellar evolution to the evolution of an entire galaxy. Regardless of the fact that they are so close, for many Milky Way clusters it is difficult to be observed because they are obscured by the dust in the disk of our Galaxy. The clusters from the Local Group and beyond are too distant, so only their integrated properties could be used most of the time. There is one way to analyze the observational data, to search for clusters, and to describe them: simulations. MASSCLEAN (MASSive CLuster Evolution and ANalysis) package was developed to provide a better characterization of Galactic clusters, to derive selection effects of current surveys, and to provide information about the extra-galactic clusters. Simulations of known Galactic clusters are used to get better constraints on their parameters, like mass, age, extinction, chemical composition and distance. This is the traditional way to describe the Galactic clusters, fitting the data using the available models. The difference is that MASSCLEAN simulations provide a consistent set of parameters. The majority of extra-galactic clusters are known only from their integrated properties, integrated magnitudes and colors. The current models for stellar populations are available only in the infinite mass limit. But the real clusters have a finite mass, and their integrated colors show a large dispersion (stochastic fluctuations). The description of the variation of integrated colors as a function of mass and age lead to the creation of MASSCLEANcolors database, based on 70 million Monte Carlo simulations. Since the entries in the database form a consistent set of integrated colors, integrated magnitudes, age and mass, they can be used to inprove the current age and mass determinations for extra-galactic clusters. The accuracy could be inproved only by solving for age and mass together, and this is done by MASSCLEANage. An introduction to stellar clusters is presented in Chapter 1. A general description of the MASSCLEAN package is presented in Chapter 2, including its Galactic and extra-galactic applications. New search algorithms for stellar clusters and derivation of selection effects for current surveys should be based on cluster simulations. The variation of the integrated colors for stellar clusters as a function of mass and age is presented in Chapter 3. The color dispersion is presented as standard deviation. The entire distribution of integrated colors is presented in Chapter 4, along with MASSCLEAN age and new values for age and mass for 37 LMC clusters. A larger population of LMC clusters with new estimations for age and mass is presented in Chapter 5. The new results for 600 clusters provide a new look to the LMC cluster population. The complete results for over 900 known clusters could be used to study the possible mass dependence of the cluster lifetime, dissolution time and infant mortality.
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