First Sagittarius A* Event Horizon Telescope Results. IV. Variability, Morphology, and Black Hole Mass

In this paper we quantify the temporal variability and image morphology of the horizon-scale emission from Sgr A*, as observed by the EHT in 2017 April at a wavelength of 1.3 mm. We find that the Sgr A* data exhibit variability that exceeds what can be explained by the uncertainties in the data or by the effects of interstellar scattering. The magnitude of this variability can be a substantial fraction of the correlated flux density, reaching similar to 100% on some baselines. Through an exploration of simple geometric source models, we demonstrate that ring-like morphologies provide better fits to the Sgr A* data than do other morphologies with comparable complexity. We develop two strategies for fitting static geometric ring models to the time-variable Sgr A* data; one strategy fits models to short segments of data over which the source is static and averages these independent fits, while the other fits models to the full data set using a parametric model for the structural variability power spectrum around the average source structure. Both geometric modeling and image-domain feature extraction techniques determine the ring diameter to be 51.8 +/- 2.3 mu as (68% credible intervals), with the ring thickness constrained to have an FWHM between similar to 30% and 50% of the ring diameter. To bring the diameter measurements to a common physical scale, we calibrate them using synthetic data generated from GRMHD simulations. This calibration constrains the angular size of the gravitational radius to be 4.8(-0.7)(+1.4) mu as, which we combine with an independent distance measurement from maser parallaxes to determine the mass of Sgr A* to be 4.0(-0.6)(+1.1) x 10(6) M-circle dot.

Automated summary

This paper quantifies the temporal variability and image morphology of the horizon-scale emission from Sgr A* observed by the EHT in 2017. It finds that the data exhibit significant variability exceeding uncertainties and scattering effects. Geometric ring models provide better fits to the data, and the diameter and thickness of the ring are determined through modeling and image-domain analysis techniques.