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.

arXiv comment7 pages, 5 figures

References in corpus (17)

• 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
• First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole
• First M87 Event Horizon Telescope Results. IV. Imaging the Central Supermassive Black Hole
• First M87 Event Horizon Telescope Results. V. Physical Origin of the Asymmetric Ring
• 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
• First Sagittarius A* Event Horizon Telescope Results. V. Testing Astrophysical Models of the Galactic Center Black Hole
• First Sagittarius A* Event Horizon Telescope Results. III: Imaging of the Galactic Center Supermassive Black Hole
• 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
• The Structure and Dynamics of the Sub-parsec Scale Jet in M87 Based on 50 VLBA Observations Over 17 Years at 43 GHz
• 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 Analysis as a Tool for Characterizing Black Hole Images and Variability
• 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
• New approach to template banks of gravitational waves with higher harmonics: Reducing matched-filtering cost by over an order of magnitude
• 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