A Universal Framework for Horizon-Scale Tests of Gravity with Black Hole Shadows

TL;DR

This paper introduces an efficient, adaptable framework for analyzing black hole shadows to test gravity theories, enabling precise parameter inference from horizon-scale observations with minimal computational resources.

Contribution

The authors developed a numerically efficient, adaptive ray-tracing framework for horizon-scale gravity tests, applicable to arbitrary stationary black holes, and demonstrated its use with recent EHT data.

Findings

Constrained magnetic fields of M87* and Sgr A* consistent with previous estimates.

Achieved high-precision shadow modeling with minimal computational cost.

Supported Einstein's gravity through magnetic field measurements.

Abstract

In this Letter, we have developed a numerically efficient framework for evaluating parameters in metric theories of gravity, and applied it to constrain the horizon-scale magnetic field in the Kerr-Bertotti-Robinson (Kerr-BR) spacetime using the latest EHT observations. The method's adaptive ray-tracing strategy achieves near-linear computational efficiency without loss of numerical accuracy. Owing to this efficiency, the framework enables high precision shadow modeling at minimal computational cost and, for the first time, supports statistically robust inference of black hole parameters from horizon-scale observations for arbitrary stationary black holes. The above framework is applied to the recently obtained Kerr-BR black hole, an exact magnetized and rotating solution to the Einstein field equations. We have evaluated the horizon-scale magnetic fields of M87* and Sgr A*, with the latter showing a field strength of $93.3^{+14.7}_{-23.8}G$, consistent with the equipartition estimate of $71G$ from polarized ALMA observations, thereby supporting Einstein's gravity.