Multidimensional hierarchical tests of general relativity with gravitational waves
Haowen Zhong, Maximiliano Isi, Katerina Chatziioannou, Will M. Farr

TL;DR
This paper develops a multidimensional hierarchical testing framework for general relativity using gravitational wave data, enabling analysis of parameter correlations and providing new constraints from the latest GW catalog.
Contribution
It extends population tests of general relativity to handle multiple parameters simultaneously, allowing for more comprehensive and correlated analyses.
Findings
Joint constraints on two parameters reveal correlation structure.
The 4D formulation contains additional information compared to 2D.
GW190814 remains an outlier, influencing population results.
Abstract
Tests of general relativity with gravitational waves typically introduce parameters for putative deviations and combine information from multiple events by characterizing the population distribution of these parameters through a hierarchical model. Although many tests include multiple such parameters, hierarchical tests have so far been unable to accommodate this multidimensionality, instead restricting to separate one-dimensional analyses and discarding information about parameter correlations. In this paper, we extend population tests of general relativity to handle an arbitrary number of dimensions. We demonstrate this framework on the two-dimensional inspiral-merger-ringdown consistency test, and derive new constraints from the latest LIGO-Virgo-KAGRA catalog, GWTC-3. We obtain joint constraints for the two parameters introduced by the classic formulation of this test, revealing…
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