论文标题
强力透镜VIII的广义非依赖性表征。自动多波段特征检测以限制本地镜头属性
Generalised model-independent characterisation of strong gravitational lenses VIII. automated multi-band feature detection to constrain local lens properties
论文作者
论文摘要
正如本系列的先前论文所建立的那样，可以使用强烈的重力透镜效应引起的高度扭曲和放大多个图像的可观察物可用于限制引力透镜在图像位置处的变形特性。如果将背景源扩展并包含子结构，例如在多个图像中解决的恒星形成区域，则可以使用至少三个多个图像匹配的所有子结构可以用于推断镜头的局部扭曲属性。在这项工作中，我们将手动功能选择替换为基于Sextractor的自动化功能提取，并显示出其出色的性能。尽管它的目标是改善我们的镜头重建，但也可以采用任何其他方法。在噪声存在下，从我们的校准测试中获得了对“图像位置”定义的有价值的见解。将其应用于Galaxy CLUSTER CL0024中的五图像配置和包含汉密尔顿对象的三图配置中的五图像配置，我们分别确定了多个波段的局部镜头属性。在当前的置信度范围内，所有这些都彼此一致，从而证实了强镜的波长独立性，并提供了一种在进一步的示例中检测由微镜头和灰尘引起的偏差的工具。
As established in previous papers of this series, observables in highly distorted and magnified multiple images caused by the strong gravitational lensing effect can be used to constrain the distorting properties of the gravitational lens at the image positions. If the background source is extended and contains substructure, like star forming regions, which is resolved in multiple images, all substructure that can be matched across a minimum of three multiple images can be used to infer the local distorting properties of the lens. In this work, we replace the manual feature selection by an automated feature extraction based on SExtractor for Python and show its superior performance. Despite its aimed development to improve our lens reconstruction, it can be employed in any other approach, as well. Valuable insights on the definition of an `image position' in the presence of noise are gained from our calibration tests. Applying it to observations of a five-image configuration in galaxy cluster CL0024 and the triple-image configuration containing Hamilton's object, we determine local lens properties for multiple wavebands separately. Within current confidence bounds, all of them are consistent with each other, corroborating the wavelength-independence of strong lensing and offering a tool to detect deviations caused by micro-lensing and dust in further examples.
