MECI: A Method for Eclipsing Component Identification
MECI: A Method for Eclipsing Component Identification
复制标题
MECI：一种超越组件识别的方法
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
D. Charbonneau
中科院分区：
文献类型：
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作者：
J. Devor;D. Charbonneau
我们描述了一个自动化的方法分配最可能的物理参数的组件的食二，只使用其光度光变曲线和组合的颜色。使用传统方法，人们试图在多次迭代中优化多参数模型，以便最小化χ2值。我们提出了一种替代方法，其中一个选择对同时代的恒星从一组理论恒星模型，并比较其模拟的光变曲线和组合的颜色与观察。这种方法大大减少了需要搜索的参数空间，并允许在没有光谱数据的情况下估计组分的质量、半径和绝对量值。我们已经实现了这种方法在一个自动化的程序中使用出版的理论等时线和边缘变暗系数。由于易于自动化，这种方法适合于系统分析由大量恒星的光度时间序列组成的数据集，例如OGLE、MACHO、TrES、HAT和许多其他调查产生的数据集。
We describe an automated method for assigning the most probable physical parameters to the components of an eclipsing binary, using only its photometric light curve and combined colors. With traditional methods, one attempts to optimize a multiparameter model over many iterations, so as to minimize the χ2 value. We suggest an alternative method, in which one selects pairs of coeval stars from a set of theoretical stellar models and compares their simulated light curves and combined colors with the observations. This approach greatly reduces the parameter space over which one needs to search and allows one to estimate the components' masses, radii, and absolute magnitudes, without spectroscopic data. We have implemented this method in an automated program using published theoretical isochrones and limb-darkening coefficients. Since it is easy to automate, this method lends itself to systematic analyses of data sets consisting of photometric time series of large numbers of stars, such as those produced by OGLE, MACHO, TrES, HAT, and many others surveys.
影响因子：
3.2
作者：
V. Mannings;A. Boss;S. Russell
通讯作者：
V. Mannings;A. Boss;S. Russell