# Gravitational-Wave Localization Alone Probes AGN Origin of Stellar-Mass   Black Hole Mergers

**Authors:** I. Bartos, Z. Haiman, Z. Marka, B.D. Metzger, N.C. Stone, S. Marka

arXiv: 1701.02328 · 2018-02-07

## TL;DR

This paper demonstrates that gravitational-wave localization alone can statistically determine the association of stellar-mass black hole mergers with active galactic nuclei, revealing their potential origin despite limited electromagnetic signals.

## Contribution

The study introduces a statistical method to identify the AGN origin of black hole mergers using GW localization data, applicable to rare host populations.

## Key findings

- Fractional AGN contributions of 50-100% detectable with 70-300 events.
- Lower contributions of 25% testable with 1000 events.
- Best localized GWs (~5%) are most effective for these constraints.

## Abstract

Stellar-mass binary black hole mergers are poised to represent the majority of gravitational-wave (GW) observations by Advanced LIGO and Virgo. Probing their origin will be difficult due to the expected lack of electromagnetic emission and limited localization accuracy. Associations with rare host galaxy types -- such as active galactic nuclei (AGN) -- can nevertheless be identified statistically through spatial correlation. We show that (i) fractional contributions $f_{\rm agn}=50-100\%$ from AGN hosts to the total BBH merger rate can be statistically established with 70-300 detected events (expected in 0.5-2 years of observation with Advanced LIGO-Virgo at design sensitivity and current rate estimates); (ii) fractional contributions as low as $f_{\rm agn}=25\%$ can be tested with 1000 events ($\sim$ 5\,years of observation); (iii) the $\sim5\%$ best localized GWs drive these constraints. The presented method and results are generally applicable to binary formation channels with rare host populations.

## Full text

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## Figures

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## References

54 references — full list in the complete paper: https://tomesphere.com/paper/1701.02328/full.md

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Source: https://tomesphere.com/paper/1701.02328