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外文期刊>The Astrophysical journal
>Superresolution Interferometric Imaging with Sparse Modeling Using Total Squared Variation: Application to Imaging the Black Hole Shadow
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Superresolution Interferometric Imaging with Sparse Modeling Using Total Squared Variation: Application to Imaging the Black Hole Shadow
We propose a new imaging technique for interferometry using sparse modeling, utilizing two regularization terms: the ? 1-norm and a new function named total squared variation (TSV) of the brightness distribution. First, we demonstrate that our technique may achieve a superresolution of ~30% compared with the traditional CLEAN beam size using synthetic observations of two point sources. Second, we present simulated observations of three physically motivated static models of Sgr A* with the Event Horizon Telescope (EHT) to show the performance of proposed techniques in greater detail. Remarkably, in both the image and gradient domains, the optimal beam size minimizing root-mean-squared errors is 10% of the traditional CLEAN beam size for ? 1+TSV regularization, and non-convolved reconstructed images have smaller errors than beam-convolved reconstructed images. This indicates that TSV is well matched to the expected physical properties of the astronomical images and the traditional post-processing technique of Gaussian convolution in interferometric imaging may not be required. We also propose a feature-extraction method to detect circular features from the image of a black hole shadow and use it to evaluate the performance of the image reconstruction. With this method and reconstructed images, the EHT can constrain the radius of the black hole shadow with an accuracy of ~10%–20% in present simulations for Sgr A*, suggesting that the EHT would be able to provide useful independent measurements of the mass of the supermassive black holes in Sgr A* and also another primary target, M87.
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机译:我们提出了一种使用稀疏建模的干涉测量新成像技术,该技术利用了两个正则项: 1-范数和一个新的函数,称为亮度分布的总平方变化(TSV)。首先,我们证明了通过使用两点源的综合观测,与传统的CLEAN光束尺寸相比,我们的技术可以实现约30%的超分辨率。其次,我们使用事件地平线望远镜(EHT)对Sgr A *的三个物理激励静态模型进行了模拟观察,以更详细地展示所提出技术的性能。值得注意的是,在图像域和梯度域中,最小均方根误差的最佳光束尺寸为传统CLEAN光束尺寸的10%。 1 + TSV正则化和非卷积重建图像的误差小于波束卷积重建图像。这表明TSV与天文图像的预期物理特性非常匹配,干涉成像中可能不需要传统的高斯卷积后处理技术。我们还提出了一种特征提取方法,用于从黑洞阴影的图像中检测出圆形特征,并将其用于评估图像重建的性能。通过这种方法和重建的图像,EHT可以在目前针对Sgr A *的模拟中以约10%–20%的精度约束黑洞阴影的半径,这表明EHT将能够提供有用的独立测量结果。 Sgr A *中超质量黑洞的质量以及另一个主要目标M87。
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