论文标题
主计量分量干涉模型（PRIMO），一种用于EHT数据I的算法I：从模拟EHT观测值重建图像
Principal-Component Interferometric Modeling (PRIMO), an Algorithm for EHT Data I: Reconstructing Images from Simulated EHT Observations
论文作者
论文摘要
事件视野望远镜（EHT）的稀疏干涉覆盖范围对黑洞图像的重建和模型拟合构成了重大挑战。 Primo是一种基于图像重建的基于分析的主要组件分析算法，它使用了高毛发性积聚流的高保真一般相对论，磁性水力动力学模拟作为训练集。这允许重建与干涉数据一致的图像，并且生活在模拟跨越的图像空间中。 Primo遵循Monte Carlo Markov链，以适合源自模拟图像集合到干涉数据的主组件的线性组合。我们表明，即使模拟参数与用于生成主组件的图像集合的仿真参数显着不同，Primo可以有效，准确地重建几个模拟图像的合成EHT数据集。所得的重建达到的分辨率与阵列的性能一致，并且不会在图像特征（例如发射环的直径）中引入明显的偏见。
The sparse interferometric coverage of the Event Horizon Telescope (EHT) poses a significant challenge for both reconstruction and model fitting of black-hole images. PRIMO is a new principal components analysis-based algorithm for image reconstruction that uses the results of high-fidelity general relativistic, magnetohydrodynamic simulations of low-luminosity accretion flows as a training set. This allows the reconstruction of images that are both consistent with the interferometric data and that live in the space of images that is spanned by the simulations. PRIMO follows Monte Carlo Markov Chains to fit a linear combination of principal components derived from an ensemble of simulated images to interferometric data. We show that PRIMO can efficiently and accurately reconstruct synthetic EHT data sets for several simulated images, even when the simulation parameters are significantly different from those of the image ensemble that was used to generate the principal components. The resulting reconstructions achieve resolution that is consistent with the performance of the array and do not introduce significant biases in image features such as the diameter of the ring of emission.
