History-Conditioned Inference of Memory and Stochastic Forcing in Generalized Langevin Equations under Lévy Noise
Lévy 噪声下广义朗之万方程的历史条件化记忆与随机驱动推断
We consider the identification of memory and stochastic forcing in a one-dimensional generalized Langevin equation with state-dependent Brownian noise and optional additive symmetric $α$-stable jumps. A finite-dimensional Markov embedding provides Kramers--Moyal conditional moment relations that separate memory drift, Brownian diffusion, and jump contributions. From increment ensembles conditioned on the observed velocity history, truncated statistics estimate the stable…