Abstract:The aim of this application is to build link between the multiobjective optimization algorithm (MultiDIRECT) and the stellar evolution code Star2003 (Helmut Schlattl) in order to find a stellar classification through a parameter identification method.<br>
Parameter identification of stellar models is a challenging task.<br> The increasing precision achieved in the determination of atmospheric parameters, coupled to the fast growing
amount of available seismic and interferometric data, has allowed to improve the constraints on stellar models.<br>
However, it is also important to improve the methods for stellar parameter estimation. <br>Stellar models are known to be highly nonlinear. Therefore, many optimization methods may
fail in computing the optimum parameters. Moreover, it is usually difficult to associate a confidence level to the inferred stellar parameters.<br>
In this application we consider the use of multiobjective optimization algorithm MultiDirect to address this problem. This method offer the advantage of being efficient for non-linear models and allow to consider constraints and goals independently.
<BR><BR><B>Software requirements</B>: linux, Intel Fortran compiler, GCC, Star2003^