A flexible Gaussian process reconstruction method and the mass function of the coalescing binary black hole systems
Yin-Jie Li, Yuan-Zhu Wang, Ming-Zhe Han, Shao-Peng Tang, Qiang Yuan,, Yi-Zhong Fan, and Da-Ming Wei

TL;DR
This paper introduces a nonparametric Gaussian process method to reconstruct the mass distribution of binary black holes from gravitational wave data, revealing features like peaks around 20-30 solar masses and estimating merger rates.
Contribution
A novel flexible Gaussian process approach for reconstructing binary black hole mass functions directly from observational data, avoiding prespecified distribution forms.
Findings
Reconstructed a peak at 20-30 solar masses in the chirp mass distribution.
Identified possible peaks below 20 solar masses.
Estimated BBH merger rate as approximately 26 Gpc^{-3} yr^{-1}.
Abstract
We develop a new method based on Gaussian process to reconstruct the mass distribution of binary black holes (BBHs). Instead of prespecifying the formalisms of mass distribution, we introduce a more flexible and nonparametric model with which the distribution can be mainly determined by the observed data. We first test our method with simulated data, and find that it can well recover the injected distribution. Then we apply this method to analyze the data of BBHs' observations from LIGO-Virgo Gravitational-Wave Transient Catalog 2. By reconstructing the chirp mass distribution, we find that there is a peak or a platform locating at rather than a single-power-law-like decrease from low mass to high mass. Moreover, one or two peaks in the chirp mass range of may be favored by the data. Assuming a mass-independent mass ratio distribution of…
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