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arXiv 1702.02601astro-ph.CO
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基于元校准的弱透镜剪切测量

Practical Weak Lensing Shear Measurement with Metacalibration

Erin S. Sheldon, Eric M. Huff

摘要:

元校准是最近引入的一种方法,仅使用可用的成像数据来精确地测量弱引力透镜剪切,而不需要关于星系属性的先验信息或来自模拟的校准。该方法涉及用小的已知剪切使图像失真,并计算剪切估计器对所施加的剪切的响应。该方法被证明是准确的,在中等大小的模拟与星系图像,具有相对较高的信噪比,没有显着的选择效果。在这项工作中,我们引入了一个形式主义来纠正剪切响应和选择偏差。我们还观察到,对于具有相对低的信噪比的图像,在元校准过程中产生的相关噪声导致显著的偏差,为此我们开发了一个简单的经验校正。为了测试这种形式主义,我们基于参数模型和真实星系图像创建了大型图像模拟,包括使用真实点扩散函数的测试。我们在百分之五的水平上改变了点扩散函数的椭圆率。在每个模拟中,我们对星系图像施加了一个小的,百分之几的剪切。我们介绍了真实数据中出现的其他挑战,例如检测阈值,恒星污染和缺失数据。我们对测量的星系属性进行了切割,以诱导显着的选择效应。使用我们的形式主义,我们恢复了输入剪切的精度优于千分之一在所有情况下。

英文摘要:

Metacalibration is a recently introduced method to accurately measure weak gravitational lensing shear using only the available imaging data, without need for prior information about galaxy properties or calibration from simulations. The method involves distorting the image with a small known shear, and calculating the response of a shear estimator to that applied shear. The method was shown to be accurate in moderate sized simulations with galaxy images that had relatively high signal-to-noise ratios, and without significant selection effects. In this work we introduce a formalism to correct for both shear response and selection biases. We also observe that, for images with relatively low signal-to-noise ratios, the correlated noise that arises during the metacalibration process results in significant bias, for which we develop a simple empirical correction. To test this formalism, we created large image simulations based on both parametric models and real galaxy images, including tests with realistic point-spread functions. We varied the point-spread function ellipticity at the five percent level. In each simulation we applied a small, few percent shear to the galaxy images. We introduced additional challenges that arise in real data, such as detection thresholds, stellar contamination, and missing data. We applied cuts on the measured galaxy properties to induce significant selection effects. Using our formalism, we recovered the input shear with an accuracy better than a part in a thousand in all cases.

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