Unlocking New Paths for Science with Extreme-Mass-Ratio Inspirals: Machine Learning-Enhanced MCMC for Accurate Parameter Inversion

arXiv:2508.00348 · gr-qc, astro-ph.CO, astro-ph.IM, physics.space-ph · Submitted 2026-08-19 · Read on arXiv

Bo Liang, Chang Liu, Hanlin Song, Zhenwei Lyu, Minghui Du, Peng Xu, Ziren Luo, Sensen He, Haohao Gu, Tianyu Zhao, Manjia Liang, Yuxiang Xu, Li-e Qiang, Mingming Sun, Wei-Liang Qian

gr-qc, astro-ph.CO, astro-ph.IM, physics.space-ph

Submitted: 2026-08-19

Updated: 2026-08-20

Code: https://github.com/mikekatz04/lisa-on-gpu

Terminology

• Normalizing Flow — 11× in this paper · explained in 3 episodes
• Flow Matching — 10× in this paper · explained in 8 episodes
• Normalizing Flows — 10× in this paper · explained in 4 episodes
• Bayesian Inference — 7× in this paper · explained in 5 episodes
• Continuous Normalizing Flow — 7× in this paper
• Accuracy — 6× in this paper · explained in 1 episode
• Markov Chain Monte Carlo — 6× in this paper
• Consistency — 4× in this paper · explained in 3 episodes
• Bayesian Framework — 3× in this paper · explained in 3 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Accretion Physics — 1× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Computational Tractability — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Degeneracy — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Fast Fourier Transform — 1× in this paper
• Flow Matching Posterior Estimation — 1× in this paper
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes
• Simulation-based Inference — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Laser Interferometer Space Antenna
• Probing fundamental physics with Extreme Mass Ratio Inspirals: a full Bayesian inference for scalar charge
• Constraining the Deviation of Kerr Metric via Bumpy Parameterization and Particle Swarm Optimization in Extreme Mass-Ratio Inspirals
• Disks, spikes, and clouds: distinguishing environmental effects on BBH gravitational waveforms
• EMRI_MC: A GPU-based Python code for Bayesian inference of EMRI waveforms
• Flow Matching for Generative Modeling
• An efficient GPU-accelerated multi-source global fit pipeline for LISA data analysis
• Black hole perturbation theory and gravitational self-force
• Accuracy Requirements: Assessing the Importance of First Post-Adiabatic Terms for Small-Mass-Ratio Binaries
• Fast $\epsilon$-free Inference of Simulation Models with Bayesian Conditional Density Estimation
• Rapid Parameter Estimation for Merging Massive Black Hole Binaries Using Continuous Normalizing Flows
• Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling
• Neural Ordinary Differential Equations

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