# A Parametric model for the shapes of black-hole shadows in non-Kerr spacetimes

## TL;DR

This paper introduces a parametric framework for modeling black-hole shadows in non-Kerr spacetimes, enabling tests of the Kerr hypothesis using EHT observations through PCA-based analysis.

## Contribution

It develops an efficient parametric model and PCA method to analyze black-hole shadows, facilitating constraints on deviations from Kerr metrics with observational data.

## Key findings

- PCA can reconstruct non-Kerr shadows with few components
- Shadow PCA amplitudes relate smoothly to metric parameters
- Framework enables testing Kerr hypothesis with EHT data

## Abstract

The Event Horizon Telescope (EHT) is taking the first images of black holes resolved at horizon scales to measure their shadows and probe accretion physics. A promising avenue for testing the hypothesis that astrophysical black holes are described by the Kerr solution to Einstein's equations is to compare the size and shape of the shadow a black hole casts on the surrounding emission to the predictions of the Kerr metric. We develop here an efficient parametric framework to perform this test. We carry out ray-tracing simulations for several parametrized non-Kerr metrics to create a large data set of non-Kerr shadows that probe the allowed parameter space for the free parameters of each metric. We then perform principal components analysis (PCA) on this set of shadows and show that only a small number of components are needed to accurately reconstruct all shadows within the set. We further show that the amplitude of the PCA components are smoothly related to the free parameters in the metrics, and therefore, that these PCA components can be fit to EHT observations in order to place constraints on the free parameters of these metrics that will help quantify any potential deviations from the Kerr solution.