Black hole parameter estimation with synthetic Very Long Baseline Interferometry data from the ground and from space
Freek Roelofs, Christian M. Fromm, Yosuke Mizuno, Jordy Davelaar,, Michael Janssen, Ziri Younsi, Luciano Rezzolla, Heino Falcke

TL;DR
This study assesses how future ground and space-based Very Long Baseline Interferometry (VLBI) observations can improve black hole parameter estimation, demonstrating significant gains from array expansion, high-frequency data, and repeated observations.
Contribution
It introduces a comprehensive simulation framework to evaluate the impact of future VLBI arrays and frequencies on black hole parameter constraints, including tests of general relativity.
Findings
Repeated observations improve parameter constraints.
High-frequency space VLBI data strongly constrain models.
Expanded arrays significantly enhance estimation accuracy.
Abstract
The Event Horizon Telescope (EHT) has imaged the shadow of the supermassive black hole in M87. A library of general relativistic magnetohydrodynamics (GMRHD) models was fit to the observational data, providing constraints on black hole parameters. We investigate how much better future experiments can realistically constrain these parameters and test theories of gravity. We generate realistic synthetic 230 GHz data from representative input models taken from a GRMHD image library for M87, using the 2017, 2021, and an expanded EHT array. The synthetic data are run through a data reduction pipeline used by the EHT. Additionally, we simulate observations at 230, 557, and 690 GHz with the Event Horizon Imager (EHI) Space VLBI concept. Using one of the EHT parameter estimation pipelines, we fit the GRMHD library images to the synthetic data and investigate how the black hole parameter…
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