论文标题
非线性Langevin系统的总变化中的截止现象,具有较小的分层噪声
The cutoff phenomenon in total variation for nonlinear Langevin systems with small layered stable noise
论文作者
论文摘要
本文提供了针对原型类的非线性Langevin系统的截止现象的扩展案例研究,其单个稳定状态受到添加剂纯跳跃lévy噪声$ \ VAREPSILON> 0 $的影响,其中驱动噪声过程是分层稳定的类型。在漂移的胁迫条件下,相关的过程家族$ x^\ varepsilon $ juts在总变化距离中以平衡分布为指数,具有平衡分布$μ^{\ varepsilon} $,从而扩展了Peng和Zhang(2018)(2018)的结果。主要结果在blumenthal-Getoor指数$α> 3/2 $的足够平滑条件下,建立了相对于总变异的截止现象。也就是说,在这种情况下,我们确定确定的时间尺度$ \ Mathfrak {t} _ {\ varepsilon}^{\ Mathrm {cut}} $满足$ \ Mathfrak { \ rightarrow 0 $,以及一个相应的时间窗口,$ \ mathfrak {t} _ \ varepsilon^{\ mathrm {cut}}} \ pm o(\ mathfrak {\ mathfrak {t} _ \ varepsilon $μ^{\ varepsilon} $本质上倒塌为$ \ varepsilon $趋于零。此外,我们将这种距离与Barrera和Jara(2020)在非线性漂移的Lévy情况下首先建立的距离的距离融合到独特的曲线函数可以描述后一种现象。这会导致足够的条件,可以在示例中进行验证,例如梯度系统受到$α> 3/2 $的小对称$α$稳定的噪声。由于缺乏各自的吉尔萨诺夫(Girsanov)变换,这些证明技术与高斯案例完全不同,这些吉尔萨诺夫(Girsanov)将非线性方程式逐渐划分,即使在短时间内渐近地近似线性近似。
This paper provides an extended case study of the cutoff phenomenon for a prototypical class of nonlinear Langevin systems with a single stable state perturbed by an additive pure jump Lévy noise of small amplitude $\varepsilon>0$, where the driving noise process is of layered stable type. Under a drift coercivity condition the associated family of processes $X^\varepsilon$ turns out to be exponentially ergodic with equilibrium distribution $μ^{\varepsilon}$ in total variation distance which extends a result from Peng and Zhang (2018) to arbitrary polynomial moments. The main results establish the cutoff phenomenon with respect to the total variation, under a sufficient smoothing condition of Blumenthal-Getoor index $α>3/2$. That is to say, in this setting we identify a deterministic time scale $\mathfrak{t}_{\varepsilon}^{\mathrm{cut}}$ satisfying $\mathfrak{t}_ \varepsilon^{\mathrm{cut}} \rightarrow \infty$, as $\varepsilon \rightarrow 0$, and a respective time window, $\mathfrak{t}_\varepsilon^{\mathrm{cut}} \pm o(\mathfrak{t}_\varepsilon^{\mathrm{cut}})$, during which the total variation distance between the current state and its equilibrium $μ^{\varepsilon}$ essentially collapses as $\varepsilon$ tends to zero. In addition, we extend the dynamical characterization under which the latter phenomenon can be described by the convergence of such distance to a unique profile function first established in Barrera and Jara (2020) to the Lévy case for nonlinear drift. This leads to sufficient conditions, which can be verified in examples, such as gradient systems subject to small symmetric $α$-stable noise for $α>3/2$. The proof techniques differ completely from the Gaussian case due to the absence of respective Girsanov transforms which couple the nonlinear equation and the linear approximation asymptotically even for short times.