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Principal-component Interferometric Modeling (PRIMO), an Algorithm for EHT Data. I. Reconstructing Images from Simulated EHT Observations
DOI:10.3847/1538-4357/acaa9a.png)
摘要
En 中文
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 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.
Keyword:
M87 EVENT HORIZON
BLACK-HOLE IMAGES
GRMHD SIMULATIONS
MAGNETOHYDRODYNAMIC SIMULATIONS
ACCRETION
VARIABILITY
SHADOW
MASS
期刊
IF:
5.4
论文数:
8.3W
被引数:
32.0W
机构
引用论文
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First M87 Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole第一个M87事件视界望远镜的结果。I.超大质量黑洞的阴影

