Using iron line reverberation and spectroscopy to distinguish Kerr and non-Kerr black holes

TL;DR

This paper explores how iron line reverberation measurements, enabled by future high-resolution X-ray observations, can enhance tests of the Kerr metric around black holes beyond traditional spectral analysis.

Contribution

It demonstrates that iron line reverberation can significantly improve constraints on black hole spacetime geometry, especially with next-generation X-ray data.

Findings

Reverberation measurements can improve constraints on black hole metrics.

Current X-ray data are insufficient for strong Kerr tests.

Next-generation data could enhance constraints by an order of magnitude.

Abstract

The iron K$\alpha$ line commonly observed in the X-ray spectrum of both stellar-mass and supermassive black hole candidates is produced by the illumination of a cold accretion disk by a hot corona. In this framework, the activation of a new flaring region in the hot corona imprints a time variation on the iron line spectrum. Future X-ray facilities with high time resolution and large effective areas may be able to measure the so-called 2-dimensional transfer function; that is, the iron line profile detected by a distant observer as a function of time in response to an instantaneous flare from the X-ray primary source. This work is a preliminary study to determine if and how such a technique can provide more information about the spacetime geometry around the compact object than the already possible measurements of the time-integrated iron line profile. Within our simplified model, we find that a measurement of iron line reverberation can improve constraints appreciably given a sufficiently strong signal, though that most of the information is present in the time-integrated spectrum. Our aim is to test the Kerr metric. We find that current X-ray facilities and data are unable to provide strong tests of the Kerr nature of supermassive black hole candidates. We consider an optimistic case of $10^5$ iron line photons from a next-generation data set. With such data, the reverberation model improves upon the spectral constraint by an order of magnitude.