论文标题
用于群集镜头源重建的多功能工具。 I. Hubble Frontier Field Field cluster Mac中的方法和插图J0717.5+3745
A versatile tool for cluster lensing source reconstruction. I. methodology and illustration on sources in the Hubble Frontier Field Cluster MACS J0717.5+3745
论文作者
论文摘要
我们描述了一种通用方法,可以重建由星系前簇的重力潜力镜头镜头的内在特性。该工具镜结构是在公开可用的多功能引力透镜软件镜头中实现的,以便为这种常见的天体物理问题提供简单快速的解决方案。该工具基于向前建模源在图像平面中的外观,考虑到镜头和仪器点扩散函数(PSF)的失真。对于单成像的来源,需要以哈勃前沿场(HFF)镜头图的格式作为起点。对于乘象的来源,该工具还可以首先适合并应用(偏转),第二(剪切,收敛)和三阶(屈曲)校正局部重力潜力,以改善重建的重建,具体取决于数据的质量。我们用五个不同的公开群集模型开始说明了代码的性能和功能,其中有两个从哈勃前沿字段获得的乘数模仿系统的示例。我们发现,经过校正后,多个图像之间的相对放大倍数以及其他镜头特性得到了强大的约束。此外,我们发现重建的源大小和大小的模型之间的散射减少了。代码和Jupyter笔记本电脑可公开使用。
We describe a general purpose method to reconstruct the intrinsic properties of sources lensed by the gravitational potential of foreground clusters of galaxies. The tool Lenstruction is implemented in the publicly available multi-purpose gravitational lensing software Lenstronomy, in order to provide an easy and fast solution to this common astrophysical problem. The tool is based on forward modeling the appearance of the source in the image plane, taking into account the distortion by lensing and the instrumental point spread function (PSF). For singly-imaged sources a global lens model in the format of the Hubble Frontier Fields (HFF) lensing maps is required as a starting point. For multiply-imaged sources, the tool can also fit and apply first (deflection), second (shear, convergence), and third order (flexion) corrections to the local gravitational potential to improve the reconstruction, depending on the quality of the data. We illustrate the performance and features of the code with two examples of multiply-imaged systems taken from the Hubble Frontier Fields, starting from five different publicly available cluster models. We find that, after our correction, the relative magnification - and other lensing properties - between the multiple images become robustly constrained. Furthermore, we find that scatter between models of the reconstructed source size and magnitude is reduced. The code and jupyter notebooks are publicly available.