Forecasting constraints on the no-hair theorem from the stochastic gravitational wave background
Abstract
Although the constraints on general relativity (GR) from each individual gravitational-wave (GW) event can be combined to form a cumulative estimate of the deviations from GR, the ever-increasing number of GW events used also leads to the ever-increasing computational cost during the parameter estimation. Therefore, in this paper, we will introduce the deviations from GR into GWs from all events in advance and then create a modified stochastic gravitational-wave background (SGWB) to perform tests of GR. More precisely, we use the model to include the model-independent hairs and calculate the corresponding SGWB with a given merger rate. Then we turn to the Fisher information matrix to forecast the constraints on the no-hair theorem from SGWB at frequency detected by the third-generation ground-based GW detectors, such as the Cosmic Explorer. We find that the forecasting constraints on hairs at confidence range are and when the flat priors about the merger rate are added but and when the non-flat priors about the merger rate are added.
Keywords
Cite
@article{arxiv.2311.17767,
title = {Forecasting constraints on the no-hair theorem from the stochastic gravitational wave background},
author = {Chen Tan and Ke Wang},
journal= {arXiv preprint arXiv:2311.17767},
year = {2024}
}
Comments
12 pages, 8 figures