A new framework for understanding systematic errors in cluster lens modelling – II. Constraint selection
A new framework for understanding systematic errors in cluster lens modelling – II. Constraint selection
复制标题
用于理解簇透镜建模中系统误差的新框架 – II。
DOI：
10.1093/mnras/stab2858
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发表时间：
2021
影响因子：
4.8
通讯作者：
Raney, Catie A
中科院分区：
文献类型：
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作者：
Zimmerman, Dhruv T;Keeton, Charles R;Raney, Catie A
集束透镜模型受透镜建模过程中的各种选择的影响。我们已经开始了一项计划，为集群透镜建模制定系统误差预算。在这里，我们研究图像约束的选择作为潜在的系统效应。为了约束质量模型，我们发现图像在星团周围的空间分布比它们在红移中分布更重要。我们还发现，一些图像集似乎比其他图像集更重要，因为它们对模型的约束程度有多好；“重要的”图像集通常包括靠近透镜临界曲线的图像以及与其他图像相对隔离的图像(在否则将缺乏透镜信息的区域中提供约束)。这些结论有助于指导为候选透镜图像寻找后续数据的观测计划。
Cluster lens models are affected by a variety of choices in the lens modelling process. We have begun a programme to develop a systematic error budget for cluster lens modelling. Here, we examine the selection of image constraints as a potential systematic effect. For constraining the mass model, we find that it is more important to have images be spatially distributed around the cluster than to have them distributed in redshift. We also find that some image sets appear to be more important than others in terms of how well they constrain the models; the ‘important’ image sets typically include an image that lies close to a lensing critical curve as well as an image that is relatively isolated from other images (providing constraints in a region that would otherwise lack lensing information). These conclusions can help guide observing programmes that seek follow-up data for candidate lensed images.