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Abstract The Event Horizon Telescope (EHT) images of the supermassive black hole at the center of the galaxy M87 provided the first image of the accretion environment on horizon scales. General relativity (GR) predicts that the image of the shadow should be nearly circular given the inclination angle of the black hole M87*. A robust detection of ellipticity in image reconstructions of M87* could signal new gravitational physics on horizon scales. Here we analyze whether the imaging parameters used in EHT analyses are sensitive to ring ellipticity, and measure the constraints on the ellipticity of M87*. We find that the top set is unable to recover ellipticity. Even for simple geometric models, the true ellipticity is biased low, preferring circular rings. Therefore, to place a constraint on the ellipticity of M87*, we measure the ellipticity of 550 synthetic data sets produced from GRMHD simulations. We find that images with intrinsic axis ratios of 2:1 are consistent with the ellipticity seen from EHT image reconstructions.
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Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors
Abstract Reconstructing images from the Event Horizon Telescope (EHT) observations of M87*, the supermassive black hole at the center of the galaxy M87, depends on a prior to impose desired image statistics. However, given the impossibility of directly observing black holes, there is no clear choice for a prior. We present a framework for flexibly designing a range of priors, each bringing different biases to the image reconstruction. These priors can be weak (e.g., impose only basic natural-image statistics) or strong (e.g., impose assumptions of black hole structure). Our framework uses Bayesian inference with score-based priors, which are data-driven priors arising from a deep generative model that can learn complicated image distributions. Using our Bayesian imaging approach with sophisticated data-driven priors, we can assess how visual features and uncertainty of reconstructed images change depending on the prior. In addition to simulated data, we image the real EHT M87* data and discuss how recovered features are influenced by the choice of prior.
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- PAR ID:
- 10553645
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 975
- Issue:
- 2
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 201
- Size(s):
- Article No. 201
- Sponsoring Org:
- National Science Foundation
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