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  • 标题:A method to deconvolve stellar rotational velocities II - The probability distribution function via Tikhonov regularization
  • 其他标题:The probability distribution function via Tikhonov regularization
  • 本地全文:下载
  • 作者:Alejandra Christen ; Alejandra Christen ; Pedro Escarate
  • 期刊名称:Astronomy & Astrophysics
  • 印刷版ISSN:0004-6361
  • 电子版ISSN:1432-0746
  • 出版年度:2016
  • 卷号:595
  • 页码:1-8
  • DOI:10.1051/0004-6361/201629070
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Aims. Knowing the distribution of stellar rotational velocities is essential for understanding stellar evolution. Because we measure the projected rotational speed v sin i, we need to solve an ill-posed problem given by a Fredholm integral of the first kind to recover the “true” rotational velocity distribution. Methods. After discretization of the Fredholm integral we apply the Tikhonov regularization method to obtain directly the probability distribution function for stellar rotational velocities. We propose a simple and straightforward procedure to determine the Tikhonov parameter. We applied Monte Carlo simulations to prove that the Tikhonov method is a consistent estimator and asymptotically unbiased. Results. This method is applied to a sample of cluster stars. We obtain confidence intervals using a bootstrap method. Our results are in close agreement with those obtained using the Lucy method for recovering the probability density distribution of rotational velocities. Furthermore, Lucy estimation lies inside our confidence interval. Conclusions. Tikhonov regularization is a highly robust method that deconvolves the rotational velocity probability density function from a sample of v sin i data directly without the need for any convergence criteria.
  • 关键词:stars: rotation;methods: statistical;methods: numerical;methods: data analysis;stars: fundamental parameters
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