主序星的V波段经验质光关系

发布时间：2018-10-08 19:37

【摘要】：恒星质量是恒星物理以及恒星系统动力学研究中一个不可或缺的参量.双星轨道拟合是获取恒星(动力学)质量的最可靠途径,而绝大部分恒星的质量仍然需要通过恒星质光关系来估计,因此,通过拟合恒星动力学质量和光度数据得到经验质光关系的工作具有重要意义.尽管主序星的V波段质光关系由于金属丰度的影响而具有一定的弥散性,但有研究表明这种影响主要限于恒星质量小于0.6M_⊙的情况.对于较大质量的主序星,近年来的观测拟合研究积累了比较充分的动力学质量和V波段光度数据,从而为显著改进上述质光关系提供了可能.利用一个能合理分配两个不同量纲观测量权重的拟合方法,根据203颗恒星的动力学质量和光度数据给出了主序星的V波段经验质光关系,该结果对此前结果的改进不仅具有统计显著性,而且其对恒星质量估计的相对误差已达到约5%.因此,该结果不仅可以用于开展有关恒星物理或恒星系统动力学方面的统计性研究,而且对具体实际多星系统的长期动力学研究和短期定位研究等也有应用价值.
[Abstract]:Stellar mass is an indispensable parameter in the study of stellar physics and stellar system dynamics. Binary orbit fitting is the most reliable way to obtain stellar mass, and the mass of most stars still needs to be estimated by the relationship between stellar mass and light. It is of great significance to obtain empirical quality-light relationship by fitting the mass and photometric data of star dynamics. Although the V-band mass-light relationship of the main ordered star has a certain dispersion due to the influence of metal abundance, some studies have shown that this influence is mainly limited to the case of star mass less than 0.6 M- _ 298. For the larger mass star, the observational fitting research in recent years has accumulated sufficient kinetic mass and V band photometric data, which provides the possibility to improve the relationship between the mass and light. Based on the kinetic mass and photometric data of 203 stars, a fitting method that can reasonably allocate the weights of two different dimensional observations is used to give the empirical mass-light relationship in V band of the principal ordered star. The improvement from the previous results is statistically significant, and the relative error of the estimation of star mass has reached about 5%. Therefore, the results can be used not only for the statistical study of stellar physics or stellar system dynamics, but also for the long-term dynamics research and short-term positioning study of practical multi-star systems.
【作者单位】：中国科学院紫金山天文台;中国科学院研究生院;
【基金】：国家自然科学基金(10473025,10833001,10703014)项目资助
【分类号】：P144.1

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