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arXiv · 2506.05954

MatBYIB: A Matlab-based code for Bayesian inference of extreme mass-ratio inspiral binary with arbitrary eccentricity

Gen-Liang Li·Shu-Jie Zhao·Huai-Ke Guo·Jing-Yu Su·Zhen-Heng Lin
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Abstract

Accurate parameter estimation(PE) of gravitational waves(GW) is essential for GW data analysis. In extreme mass-ratio inspiral binary(EMRI) systems, orbital eccentricity is a critical parameter for PE. However, current software for for PE of GW often neglects the direct estimation of orbital eccentricity. To fill this gap, we have developed the MatBYIB, a MATLAB-based software package for PE of GW with arbitrary eccentricity. The MatBYIB employs the Analytical Kludge (AK) waveform as a computationally efficient signal generator and computes parameter uncertainties via the Fisher Information Matrix (FIM) and the Markov Chain Monte Carlo (MCMC). For Bayesian inference, we implement the Metropolis-Hastings (M-H) algorithm to derive posterior distributions. To guarantee convergence, the Gelman-Rubin convergence criterion (the Potential Scale Reduction Factor R) is used to determine sampling adequacy, with MatBYIB dynamically increasing the sample size until R < 1.05 for all parameters. Our results demonstrate strong agreement between FIM- based predictions and full MCMC sampling. This program is user-friendly and allows for estimation of gravitational wave parameters with arbitrary eccentricity on standard personal computers. Code availability:The implementation is open-source at https://github.com/GenliangLi/MatBYIB.

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Gen-Liang Li, Shu-Jie Zhao, Huai-Ke Guo, Jing-Yu Su, Zhen-Heng Lin. 2025-06-06. MatBYIB: A Matlab-based code for Bayesian inference of extreme mass-ratio inspiral binary with arbitrary eccentricity. https://doi.org/10.3390/universe11080259

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