标题： 用自由形式建模探测暗物质亚结构：一个“ jackpot ”强透镜的案例研究 显示英文标题

标题： Probing Dark Matter Substructures with Free-Form Modelling: A Case Study of the `Jackpot' Strong Lens

摘要： 描述亚星系晕的种群和内部结构对于限制暗物质的本质至关重要。 这些晕可以通过作用于强引力透镜的星系附近被探测到，因为它们会扰动弧的形状。 然而，这种方法受到假阳性探测和系统不确定性的影响：特别是单个晕与透镜质量分布中更大尺度的不对称性之间的退化。 我们提出了一种新的自由形式透镜建模代码，该代码是在开源软件\texttt{PyAutoLens}的框架内开发的，以应对这些挑战。 我们的方法将无法通过参数模型捕获的质量扰动建模为像素化的势能校正，并通过受高斯过程回归启发的 Matérn 正则化方案抑制非物理解。 这种方法能够恢复多样的质量扰动，包括次晕、视线方向上的晕、外部剪切以及表示透镜星系复杂角质量分布的多极分量（如盒状/盘状）。 此外，我们的全贝叶斯框架客观推断与像素化源和势能校正正则化相关的超参数，消除了手动微调的需求。 通过将我们的代码应用于著名的“大 jackpot”透镜系统 SLACS0946+1006，我们稳健地检测到了一个高度集中的次晕，这挑战了标准冷暗物质模型。 本研究代表了首次尝试使用完全自由形式的方法独立揭示次晕的质量分布。 显示英文摘要

摘要： Characterising the population and internal structure of sub-galactic halos is critical for constraining the nature of dark matter. These halos can be detected near galaxies that act as strong gravitational lenses with extended arcs, as they perturb the shapes of the arcs. However, this method is subject to false-positive detections and systematic uncertainties: particularly degeneracies between an individual halo and larger-scale asymmetries in the distribution of lens mass. We present a new free-form lens modelling code, developed within the framework of the open-source software \texttt{PyAutoLens}, to address these challenges. Our method models mass perturbations that cannot be captured by parametric models as pixelized potential corrections and suppresses unphysical solutions via a Mat\'ern regularisation scheme that is inspired by Gaussian process regression. This approach enables the recovery of diverse mass perturbations, including subhalos, line-of-sight halos, external shear, and multipole components that represent the complex angular mass distribution of the lens galaxy, such as boxiness/diskiness. Additionally, our fully Bayesian framework objectively infers hyperparameters associated with the regularisation of pixelized sources and potential corrections, eliminating the need for manual fine-tuning. By applying our code to the well-known `Jackpot' lens system, SLACS0946+1006, we robustly detect a highly concentrated subhalo that challenges the standard cold dark matter model. This study represents the first attempt to independently reveal the mass distribution of a subhalo using a fully free-form approach.