Black Hole Olympics: Metric Selection from the Event Horizon Telescope and LIGO-VIRGO Observations

TL;DR

This paper introduces a new paradigm for black hole research that involves selecting the most observationally preferred metric using high-precision data from the Event Horizon Telescope and LIGO-VIRGO, applying Bayesian criteria.

Contribution

It proposes a novel approach to black hole metric selection based on observational data, ranking metrics with Bayesian information criterion, and providing constraints on black hole parameters.

Findings

Kerr and Reissner-Nordstr"{o}m} tie for first place in the black hole Olympics.

Provides upper bounds on black hole charge and spin parameters.

Current data shows no clear preference for a specific black hole metric.

Abstract

We propose a new paradigm in the field of black hole physics, i.e., with more and more high precision observations, one must make a metric selection to determine which black hole is observationally preferred. In light of the shadow imaging data from the Event Horizon Telescope and gravitational wave measurements from the LIGO-VIRGO collaboration, we attempt to address this issue. Although not finding any obvious preference for a specific black hole metric based on current data, as a presentation of this new research paradigm, we rank these black hole metrics using the Bayesian information criterion. We find that Kerr and Reissner-Nordstr\"{o}m tie the first place in the black hole Olympics Games. Interestingly, we give the $2\,\sigma$ upper bound of the average electronic charge $Q<2.82\times10^{18}$ C for the Reissner-Nordstr\"{o}m spacetime, and the $2\,\sigma$ constraint on the average spin parameter $a=-0.02^{+4.07}_{-4.04}$ m for the Kerr spacetime, which is consistent with the prediction of zero rotation for a distant observer. Future multi-messenger and multi-wavelength observations will enhance the application of this new paradigm into tests of gravitational theories and black holes.