SciELO - Scientific Electronic Library Online

 
vol.41 número1The global kinematics of the Dumbbell planetary nebula (NGC 6853, M27, PN G060.8-03.6)A simple model for hydromagnetic instabilities in the presence of a constant magnetic field índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Revista mexicana de astronomía y astrofísica

versão impressa ISSN 0185-1101

Resumo

GEORGIEV, L.  e  HERNANDEZ, X.. Determination of the mass loss rate and the terminal velocity of stellar winds. I. Genetic algorithm for automatic line profile fitting. Rev. mex. astron. astrofis [online]. 2005, vol.41, n.1, pp.121-129. ISSN 0185-1101.

A new method for automatic fitting of P Cyg line profiles in UV spectra of stellar winds is presented. The line source function is calculated using Sobolev's approximation and the emergent flux is obtained by exact integration of the equation of the radiation transport (similar to the SEI method described by Lamers et al. (1987)). The quality of the fit is evaluated using the likelihood estimator. The maximization of the likelihood is done by a genetic algorithm. The advantages of our method with respect to other similar approaches are its robustness and its insensibility to the initial guess. In addition, the algorithm guarantees the localization of the global maximum of the likelihood hypersurface, which is not the case for classical minimization algorithms. Here we present an implementation of the genetic algorithm for line profile fitting, its tests on both synthetic and real data and an estimation of the confidence limits of the results.

Palavras-chave : Line [Profiles]; Stars [Atmospheres]; Stars [winds]; Stars [outflows].

        · resumo em Espanhol     · texto em Inglês

 

Creative Commons License Todo o conteúdo deste periódico, exceto onde está identificado, está licenciado sob uma Licença Creative Commons