The Image of the M87 Black Hole Reconstructed with PRIMO

Abstract

We present a new reconstruction of the Event Horizon Telescope (EHT) image of the M87 black hole from the 2017 data set. We use PRIMO, a novel dictionary-learning based algorithm that uses high-fidelity simulations of accreting black holes as a training set. By learning the correlations between the different regions of the space of interferometric data, this approach allows us to recover high-fidelity images even in the presence of sparse coverage and reach the nominal resolution of the EHT array. The black hole image comprises a thin bright ring with a diameter of $41.5\pm 0.6\mu$as and a fractional width that is at least a factor of two smaller than previously reported. This improvement has important implications for measuring the mass of the central black hole in M87 based on the EHT images.

7 pages, 5 figures

References in corpus (15)

• First M87 Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole
• First Sagittarius A* Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole in the Center of the Milky Way
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• First M87 Event Horizon Telescope Results. IV. Imaging the Central Supermassive Black Hole
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• First M87 Event Horizon Telescope Results. II. Array and Instrumentation
• First M87 Event Horizon Telescope Results. III. Data Processing and Calibration
• First Sagittarius A* Event Horizon Telescope Results. VI: Testing the Black Hole Metric
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• First Sagittarius A* Event Horizon Telescope Results. II. EHT and Multi-wavelength Observations, Data Processing, and Calibration
• First Sagittarius A* Event Horizon Telescope Results. IV. Variability, Morphology, and Black Hole Mass
• Black Hole Images as Tests of General Relativity: Effects of Spacetime Geometry
• Black Hole Images as Tests of General Relativity: Effects of Plasma Physics
• Principal-Component Interferometric Modeling (PRIMO), an Algorithm for EHT Data I: Reconstructing Images from Simulated EHT Observations

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• Deep learning inference with the Event Horizon Telescope II. The Zingularity framework for Bayesian artificial neural networks
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• Identification of Intermediate-mass Black Hole Candidates Among a Sample of Sd Galaxies
• Interferometric Image Reconstruction using Closure Invariants and Machine Learning
• Shadows of a generic class of spherically symmetric, static spacetimes
• HST-1 as a Window to the Energetics of the Jet Spine of M87
• Charged spherically symmetric black holes in the Lyra geometry and a preliminary investigation on the overcharging process