4 papers
Estimating Orbital Parameters of Direct Imaging Exoplanet Using Neural Network
Bo Liang, Hanlin Song, Chang Liu +9
In this work, we propose a flow-matching Markov chain Monte Carlo (FM-MCMC) algorithm for estimating the orbital parameters of exoplanetary systems, especially for those only one e…
FluxMC: Rapid and High-Fidelity Inference for Space-Based Gravitational-Wave Observations
Bo Liang, Chang Liu, Hanlin Song +11
Bayesian inference in the physical sciences faces a fundamental challenge: the imperative for high-fidelity physical modeling often clashes with the intrinsic limitations of stocha…
On the mapping between bound states and black hole quasinormal modes via analytic continuation: a spectral instability perspective
Guan-Ru Li, Wei-Liang Qian, Xiao-Mei Kuang +5
In this work, we investigate the relation between bound states and quasinormal modes within black hole perturbation theory in the context of spectral instability. Our analysis indi…
Toward Efficient and Accurate EMRI Parameter Estimation: A Machine Learning-Enhanced MCMC Framework
Bo Liang, Chang Liu, Hanlin Song +13
The detection of gravitational waves from extreme-mass-ratio inspirals (EMRIs) in space-based antennas like Taiji and Laser Interferometer Space Antenna promises deep insights into…