论文标题
基于经验恒星光谱库的径向基础函数网络的升级插值网络网络
An upgraded interpolator of the radial basis functions network for spectral calculation based on empirical stellar spectral library
论文作者
论文摘要
恒星种群合成是银河系和恒星群研究中的重要方法。在恒星种群合成模型中，恒星光谱文库对于恒星种群的综合光谱是必需的。通常，恒星光谱文库用于恒星大气参数与恒星光谱之间的转换。与理论库相比，经验恒星光谱库具有不可替代的优势。但是，对于经验光谱库，在恒星大气参数空间中，恒星的分布是不规则的，这使得传统的插装器难以获得准确的结果。在这项工作中，我们将提供改进的径向基函数插值器，该插值用于获得基于经验恒星光谱文库的插值恒星光谱。对于此插值器，我们使用高斯径向基础函数中的标准方差σ与恒星大气参数空间中恒星的密度分布之间的关系，以对此σ的先验约束。此外，我们还通过恒星在恒星大气参数空间中局部分散的优势来考虑各向异性半径基础函数。此外，我们使用经验恒星光谱库英里来测试此插值器。总体而言，除了低温区域的边缘外，插装器具有良好的性能。最后，我们将这个插值器与Cheng等人的作品进行了比较。 （2018年），插值结果显示出明显的改善。用户可以使用此插值器来快速，轻松地基于恒星光谱库获取插值光谱。
Stellar population synthesis is an important method in the galaxy and star-cluster studies. In the stellar population synthesis models, stellar spectral library is necessary for the integrated spectra of the stellar population. Usually, the stellar spectral library is used to the transformation between the stellar atmospheric parameters and the stellar spectrum. The empirical stellar spectral library has irreplaceable advantages than the theoretical library. However, for the empirical spectral library, the distribution of stars is irregularly in the stellar atmospheric parameter space, this makes the traditional interpolator difficult to get the accurate results. In this work, we will provide an improved radial basis function interpolator which is used to obtain the interpolated stellar spectra based on the empirical stellar spectral library. For this interpolator, we use the relation between the standard variance σ in the Gaussian radial basis function and the density distribution of stars in the stellar atmospheric parameter space to give the prior constraint on this σ. Moreover, we also consider the anisotropic radius basis function by the advantage of the local dispersion of stars in the stellar atmospheric parameter space. Furthermore, we use the empirical stellar spectral library MILES to test this interpolator. On the whole, the interpolator has a good performance except for the edge of the low-temperature region. At last, we compare this interpolator with the work in Cheng et al. (2018), the interpolation result shows an obvious improvement. Users can use this interpolator to get the interpolated spectra based on the stellar spectral library quickly and easily.
