IR干涉测量中可靠的不确定度：相关统计误差和系统误差的引导
Towards reliable uncertainties in IR interferometry: The bootstrap for correlated statistical & systematic errors
摘要：
我们提出了一种方法，以克服通常的限制，目前的数据处理技术在光学和红外长基线干涉测量：大多数减少管道假设不相关的统计误差，忽略系统。我们使用自助法对干涉观测量的多元概率密度函数进行抽样。它使我们能够确定统计误差项与其偏离高斯分布之间的相关性。此外，我们引入系统学作为一个额外的，高度相关的误差项，其大小被选择以适应数据分散。我们已经应用该方法来获得准确的测量恒星直径的欠分辨率的恒星，即小于角分辨率的干涉仪。我们表明，采取相关性和系统学有显着的影响，直径估计和它的不确定性。我们的直径测定的鲁棒性是有代价的：我们获得了4倍的不确定性，对于我们样本中的大多数恒星来说，不确定性只有几个百分点。
英文摘要：
We propose a method to overcome the usual limitation of current data processing techniques in optical and infrared long-baseline interferometry: most reduction pipelines assume uncorrelated statistical errors and ignore systematics. We use the bootstrap method to sample the multivariate probability density function of the interferometric observables. It allows us to determine the correlations between statistical error terms and their deviation from a Gaussian distribution. In addition, we introduce systematics as an additional, highly correlated error term whose magnitude is chosen to fit the data dispersion. We have applied the method to obtain accurate measurements of stellar diameters for under-resolved stars, i.e. smaller than the angular resolution of the interferometer. We show that taking correlations and systematics has a significant impact on both the diameter estimate and its uncertainty. The robustness of our diameter determination comes at a price: we obtain 4 times larger uncertainties, of a few percent for most stars in our sample.
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