2022
DOI: 10.3847/2041-8213/ac65eb
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A Universal Power-law Prescription for Variability from Synthetic Images of Black Hole Accretion Flows

Abstract: We present a framework for characterizing the spatiotemporal power spectrum of the variability expected from the horizon-scale emission structure around supermassive black holes, and we apply this framework to a library of general relativistic magnetohydrodynamic (GRMHD) simulations and associated general relativistic ray-traced images relevant for Event Horizon Telescope (EHT) observations of Sgr A*. We find that the variability power spectrum is generically a red-noise process in both the temporal and spatia… Show more

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Cited by 28 publications
(29 citation statements)
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References 85 publications
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“…Because of the short dynamical timescale ∼ 20 s, the EHT has pushed VLBI techniques to image the dynamical evolution of Sgr A by reconstructing the source's emission region [18,19]. Assuming General Relativity, the estimated dynamical mass and distance are consistent with the angular diameter of the shadow (51.8 ± 2.3) µas recently reported by the EHT collaboration [20][21][22][23][24][25][26][27][28][29].…”
supporting
confidence: 61%
“…Because of the short dynamical timescale ∼ 20 s, the EHT has pushed VLBI techniques to image the dynamical evolution of Sgr A by reconstructing the source's emission region [18,19]. Assuming General Relativity, the estimated dynamical mass and distance are consistent with the angular diameter of the shadow (51.8 ± 2.3) µas recently reported by the EHT collaboration [20][21][22][23][24][25][26][27][28][29].…”
supporting
confidence: 61%
“…The measured s var 2 is well characterized by a power law for 2 Gλ < |u| < 6 Gλ (Georgiev et al 2022). For comparison with the models presented here, we distill the s var 2 to two numbers: the amplitude a Model predictions for a 4 2 and b are computed using the power spectral densities from Georgiev et al (2022). 160 The anisotropic diffractive scattering kernel from Johnson et al (2018) is applied to…”
Section: Eht Structural Variabilitymentioning
confidence: 83%
“…This behavior is generic across a large number of simulations of Sgr A * and explored in detail inGeorgiev et al (2022).…”
mentioning
confidence: 73%