Correcting systematic effects in a large set of photometric light curves
Correcting systematic effects in a large set of photometric light curves
复制标题
DOI：
10.1111/j.1365-2966.2004.08585.x
复制
发表时间：
2005-02
影响因子：
4.8
通讯作者：
O. Tamuz;T. Mazeh;S. Zucker
中科院分区：
文献类型：
--
作者：
O. Tamuz;T. Mazeh;S. Zucker
我们提出了一种新的算法，以消除系统的影响，在一个大的光度测量得到的光变曲线。该算法可以消除系统的影响，如与大气消光，检测器效率，或PSF的变化在检测器。该算法的工作原理没有任何先验知识的影响，只要他们线性出现在许多恒星的样本。这种方法最初是为了消除大气消光效应而开发的，它是基于矩阵的低秩近似，例如，这种方法已经被建议并用于化学计量学。该算法是特别有用的情况下，测量的不确定性是不平等的。对于相等的不确定性，该算法减少到主成分分析（PCA）算法。我们提出了一个模拟，以证明所提出的算法的有效性，并指出其潜力，特别是在寻找过境候选人。
We suggest a new algorithm to remove systematic effects in a large set of lightcurves obtained by a photometric survey. The algorithm can remove systematic effects, like the ones associated with atmospheric extinction, detector efficiency, or PSF changes over the detector. The algorithm works without any prior knowledge of the effects, as long as they linearly appear in many stars of the sample. The approach, which was originally developed to remove atmospheric extinction effects, is based on a lower rank approximation of matrices, an approach which was already suggested and used in chemometrics, for example. The proposed algorithm is specially useful in cases where the uncertainties of the measurements are unequal. For equal uncertainties the algorithm reduces to the Principal Components Analysis (PCA) algorithm. We present a simulation to demonstrate the effectiveness of the proposed algorithm and point out its potential, in search for transit candidates in particular.