论文标题
事件视野望远镜的变分图像提取
Variational Image Feature Extraction for the Event Horizon Telescope
论文作者
论文摘要
成像算法构成了用于VLBI数据分析的强大分析工具。但是，这些工具无法通过非参数性质来测量某些图像特征（例如环直径）。这是不幸的，因为这些图像特征通常与天体物理相关的数量（例如黑洞质量）有关。本文详细介绍了一种新的一般图像特征提取技术，该技术适用于称为变异图像域分析的各种VLBI图像重建。与以前的工具不同，无论其结构如何，都可以将变量图像域分析应用于任何图像重建。为了证明其灵活性，我们分析了先前EHT合成数据集的数千个重建，并恢复图像特征，例如直径，方向和不对称性。通过测量这些特征，VIDA可以帮助提取与天体物理相关的数量，例如M 87的质量和方向。
Imaging algorithms form powerful analysis tools for VLBI data analysis. However, these tools cannot measure certain image features (e.g., ring diameter) by their non-parametric nature. This is unfortunate since these image features are often related to astrophysically relevant quantities such as black hole mass. This paper details a new general image feature extraction technique that applies to a wide variety of VLBI image reconstructions called variational image domain analysis. Unlike previous tools, variational image domain analysis can be applied to any image reconstruction regardless of its structure. To demonstrate its flexibility, we analyze thousands of reconstructions from previous EHT synthetic datasets and recover image features such as diameter, orientation, and asymmetry. By measuring these features, VIDA can help extract astrophysically relevant quantities such as the mass and orientation of M 87.
