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Yanbin Zhu

Publications and source records attributed to Yanbin Zhu.

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Persistence and long-time breakdown of most probable paths under time-dependent fractional noise with applications to KAM tori

We investigate the persistence of most probable paths through the Onsager--Machlup functional for multidimensional stochastic differential equations driven by fractional Brownian motion with time-dependent diffusion coefficients and Hurst parameter $H\in(1/4,1)$. Under suitable structural and variational conditions, deterministic trajectories remain most probable paths for sufficiently small noise in both the fixed-endpoint transition problem and the free-endpoint evolution problem, whereas sufficiently large noise destroys their local minimality. More generally, when exact persistence does not hold, global most probable paths converge to the corresponding trajectories of the noise-free system in both the uniform and H\"older topologies at the rate $O(\epsilon)$. We further analyze the second variation along periodic deterministic trajectories over time intervals of length $NT$. For $H>1/2$, positive definiteness, and hence local minimality, is lost on sufficiently long intervals. For $H\in(1/4,1/2]$, long-time positive definiteness holds for the fixed-endpoint problem, but this conclusion does not directly extend to the free-endpoint setting. We also establish the persistence of KAM tori in nearly integrable Hamiltonian systems in the sense of most probable evolution paths. Finally, a two-dimensional numerical example illustrates the persistence of deterministic trajectories under small noise and their pronounced deviation under large noise.

math.PR

Onsager--Machlup Functionals for Generalized Newtonian Equations of Motion with Time-Varying Fractional Noise

In this paper, we derive the Onsager--Machlup functional for a class of degenerate stochastic differential equations on $\mathbb{R}^{m+n}$ driven by $n$-dimensional fractional Brownian motion with time-dependent diffusion coefficients, where the Hurst parameter satisfies $H\in(1/4,1)$. The main difficulty arises from the interaction between the degenerate structure and the multidimensional fractional noise, which produces nontrivial coupling terms under small-ball conditioning. By combining the Gaussian correlation inequality with an approximation argument for infinite-dimensional convex sets, we establish a decoupling mechanism that allows these coupling effects to be controlled by unconditional Gaussian expectations. Furthermore, through regularity estimates for the degenerate components and sharp H\"older norm estimates, we eliminate the remaining coupling contributions and obtain an explicit expression for the Onsager--Machlup functional. As applications of the derived functional, we obtain the corresponding constrained Euler--Lagrange equations characterizing the most probable transition paths of the system, and establish a sufficient condition under which the stochastic differential equation preserves the most probable path.

math.PR

Onsager--Machlup Functional for Fractional Stochastic Newton Dynamics with Time-Dependent Noise Intensities

In this paper, we derive the Onsager--Machlup functional for a second-order Newton-type stochastic system driven by time-dependent fractional noise, \[ X_t'' = f_t(X_t, X_t') + \sigma_t \,\xi_t^{H}, \] where \( H \in (1/4,1) \). The analysis relies on applying a Girsanov transformation to the non-degenerate components and evaluating the limiting conditional expectation associated with the noise term, for which the stochastic Fubini theorem plays a crucial role. To illustrate the applicability of the result, we study two mechanical systems perturbed by noise and provide supporting numerical simulations.

math.DS

Onsager-Machlup Functional for SDE with Time-Varying Fractional Noise

In this paper, we derive the Onsager-Machlup functional for stochastic differential equations driven by time-varying fractional noise of the form X(t) = x0 + integral from 0 to t b_s(X(s)) ds + integral from 0 to t sigma_s dB^H(s), where B^H denotes fractional Brownian motion with Hurst parameter H. Our main results are established for H in (1/4, 1) by extending small ball probability estimates and the Girsanov theorem for fractional Brownian motion to the setting with time-dependent coefficients. Regarding the choice of norms, for 1/4 < H < 1/2 the analysis is valid under the supremum norm and Holder norms of order 0 < beta < H - 1/4. For 1/2 < H < 1 the analysis applies to Holder norms of order beta satisfying H - 1/2 < beta < H - 1/4. In the case H = 1/2, the admissible norms depend on the spatial regularity of the drift coefficient b: specifically, if b is n-times continuously differentiable, then Holder norms of order 0 < beta < 1/2 - 1/(2n) are permissible. To validate our theoretical findings, we perform numerical simulations for a classical double-well potential system, illustrating how time-varying fractional noise influences transition dynamics between metastable states.

math.PR

The Onsager-Machlup functional for distribution dependent SDEs driven by fractional Brownian motion

In this paper, we compute the Onsager-Machlup functional for distribution dependent SDEs driven by fractional Brownian motions with Hurst parameter $H\in (\frac{1}{4},1)$. In the case $ \frac{1}{4} < H < \frac{1}{2} $, the norm can be either the supremum norm or H\"older norms of order $ \beta $ with $ 0 < \beta < H - \frac{1}{4} $. In the case $\frac{1}{2} < H < 1 $, the norms can be a H\"older norm of order $ \beta$ with $ H - \frac{1}{2} < \beta < H - \frac{1}{4} $. As an example, we compute the Onsager-Machlup functional for the stochastic pendulum equation

math.DS