Separating Astrophysics and Geometry in Black Hole Images

TL;DR

This paper introduces a principal component analysis-based method to disentangle the true black hole spacetime signal from confounding factors like accretion flow modeling and calibration uncertainties in black hole imaging.

Contribution

It presents a novel formalism that reconstructs the black hole metric independently of astrophysical and calibration uncertainties, enhancing tests of general relativity.

Findings

Separation of signal and foreground is feasible with next-generation EHT data.

The method effectively reconstructs the black hole metric in simulated scenarios.

Demonstrates potential to test strong-field gravity with improved imaging techniques.

Abstract

The observation of the shadow of the supermassive black hole M87$^{*}$ by the Event Horizon Telescope (EHT) is sensitive to the spacetime geometry near the circular photon orbit and beyond, and it thus has the potential to test general relativity in the strong field regime. Obstacles to this program, however, include degeneracies between putative deviations from general relativity and both the description of the accretion flow and the uncertainties on "calibration parameters", such as e.g. the mass and spin of the black hole. In this work, we introduce a formalism, based on a principal component analysis, capable of reconstructing the black hole metric (i.e. the "signal") in an agnostic way, while subtracting the "foreground" due to the uncertainties in the calibration parameters and the modelling of the accretion flow. We apply our technique to simulated mock data for spherically symmetric black holes surrounded by a thick accretion disk. We show that separation of signal and foreground may be possible with next generation EHT-like experiments.