Bayesian techniques for comparing time-dependent GRMHD simulations to variable Event Horizon Telescope observations

Abstract

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

11 pages, 8 figures, published in ApJ (replaced with accepted version)

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Cited by in corpus (23)

• First M87 Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole
• First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole
• Testing General Relativity with the Event Horizon Telescope
• The Scattering and Intrinsic Structure of Sagittarius A* at Radio Wavelengths
• Detection of intrinsic source structure at ~3 Schwarzschild radii with Millimeter-VLBI observations of SAGITTARIUS A*
• Simulations of imaging the event horizon of Sagittarius A* from space
• Strong deflection gravitational lensing by a modified Hayward black hole
• Black Hole Shadow as a Test of General Relativity: Quadratic Gravity
• Dynamical Imaging with Interferometry
• Monitoring the Morphology of M87* in 2009-2017 with the Event Horizon Telescope
• Silhouettes of invisible black holes
• Event horizon image within black hole shadow
• Black hole parameter estimation with synthetic Very Long Baseline Interferometry data from the ground and from space
• Quantifying Intrinsic Variability of Sagittarius A* using Closure Phase Measurements of the Event Horizon Telescope
• GRMHD simulations of visibility amplitude variability for Event Horizon Telescope images of Sgr A*
• GRay2: A General Purpose Geodesic Integrator for Kerr Spacetimes
• Principal Component Analysis as a Tool for Characterizing Black Hole Images and Variability
• To see invisible: image of the event horizon within the black hole shadow
• Gravitational Lensing of a star by a rotating black hole
• Event horizon silhouette: implications to supermassive black holes M87* and SgrA*
• Principal-Component Interferometric Modeling (PRIMO), an Algorithm for EHT Data I: Reconstructing Images from Simulated EHT Observations
• Deep learning inference with the Event Horizon Telescope II. The Zingularity framework for Bayesian artificial neural networks
• Visible shapes of black holes M87* and SgrA*