Panpan Ren, Shen Wang
By comparing the original equations with the corresponding stationary ones, the moderate deviation principle (MDP) is established for unbounded additive functionals of several different models of distribution dependent SDEs, with non-degenerate and degenerate noises.
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We consider a SDE with a smooth multiplicative non-degenerate noise and a possibly unbounded Holder continuous drift term. We prove existence of a global flow of diffeomorphisms by means of a special transformation of the drift of Ito-Tanaka type. The proof requires non-standard elliptic estimates in Holder spaces. As an application of the stochastic flow, we obtain a Bismut-Elworthy-Li type formula for the first derivatives of the associated diffusion semigroup.
Strong rate of convergence for the Euler--Maruyama scheme of SDEs with unbounded Hölder continuous drift coefficient
本文研究了具有无界Hölder连续漂移系数的SDEs中Euler-Maruyama方案的强收敛速率，采用Itô-Tanaka技巧和热核估计进行分析。
We study functional stochastic differential equations with a locally unbounded, functional drift focusing on well-posedness, stability and the strong Feller property. Following the non-functional case, we only consider integrability conditions and avoid continuity assumptions as far as possible. Our approach is mainly based on Zvonkin's transformation [18], an extended version of the probabilistic approach of Maslowski and Seidler [12] and the convergence concept for random variables in topological spaces in [2].
We study a stochastic differential equation with an unbounded drift and general Hölder continuous noise of an arbitrary order. The corresponding equation turns out to have a unique solution that, depending on a particular shape of the drift, either stays above some continuous function or has continuous upper and lower bounds. Under some additional assumptions on the noise, we prove that the solution has moments of all orders. We complete the study providing a numerical scheme for the solution. As an illustration of our results and motivation for applications, we suggest two stochastic volatili…
In this paper, we first prove that the existence of a solution of SDEs under the assumptions that the drift coefficient is of linear growth and path--dependent, and diffusion coefficient is bounded, uniformly elliptic and Hölder continuous. We apply Gaussian upper bound for a probability density function of a solution of SDE without drift coefficient and local Novikov condition, in order to use Maruyama--Girsanov transformation. The aim of this paper is to prove the existence with explicit representations (under linear/super--linear growth condition), Gaussian two--sided bound and Hölder conti…
Large and Moderate deviation principles for the Multivalued McKean-Vlasov SDEs with jumps
本文通过弱收敛方法研究了具有非利普希茨系数的多值麦克-瓦拉斯随机微分方程的大偏差和中等偏差原理，并利用比希-里不等式解决非利普希茨条件带来的困难。
We consider non degenerate Brownian SDEs with H{ö}lder continuous in space diffusion coefficient and unbounded drift with linear growth. We derive two sided bounds for the associated density and pointwise controls of its derivatives up to order two under some additional spatial H{ö}lder continuity assumptions on the drift. Importantly, the estimates reflect the transport of the initial condition by the unbounded drift through an auxiliary, possibly regularized, flow.
Let $(L_t)_{t \geq 0}$ be a $k$-dimensional Lévy process and $σ: \mathbb{R}^d \to \mathbb{R}^{d \times k}$ a continuous function such that the Lévy-driven stochastic differential equation (SDE) $$dX_t = σ(X_{t-}) \, dL_t, \qquad X_0 \sim μ$$ has a unique weak solution. We show that the solution is a Feller process whose domain of the generator contains the smooth functions with compact support if, and only if, the Lévy measure $ν$ of the driving Lévy process $(L_t)_{t \geq 0}$ satisfies $$ν(\{y \in \mathbb{R}^k; |σ(x)y+x|<r\}) \xrightarrow[]{|x| \to \infty} 0.$$
Heat kernel estimates for kinetic SDEs with drifts being unbounded and in Kato's class
本文证明了具有Hölder扩散和Kato类无界奇异漂移项的动理学随机微分方程弱解的存在唯一性，建立了密度的精确双边估计，并将结果应用于二阶奇异相互作用粒子系统。
Strong completeness of SDEs and non-explosion for RDEs with coefficients having unbounded derivatives
本文研究了具有无界导数的系数的SDEs强完备性与RDEs非爆炸性，证明了全局双连续解流的存在并展示了非爆炸性结果的尖锐性。
In this paper, we are interested in the following one dimensional forward stochastic differential equation (SDE) \[ d X_{t}=b(t,X_{t},ω)d t +σd B_{t},\quad 0\leq t\leq T,\quad X_{0}=\,x\in \mathbb{R}, \] where the driving noise $B_{t}$ is a $d$-dimensional Brownian motion. The drift coefficient $b:[0,T] \timesΩ\times \mathbb{R}\longrightarrow \mathbb{R}$ is Borel measurable and can be decomposed into a deterministic and a random part, i.e., $b(t,x,ω) = b_1(t,x) + b_2(t,x,ω)$. Assuming that $b_1$ is of spacial linear growth and $b_2$ satisfies some integrability conditions, we obtain the existe…
In this paper, we consider McKean-Vlasov stochastic differential equations (MVSDEs) driven by Lévy noise. By identifying the right equations satisfied by the solutions of the MVSDEs with shifted driving Lévy noise, we build up a framework to fully apply the weak convergence method to establish large and moderate deviation principles for MVSDEs. In the case of ordinary SDEs, the rate function is calculated by using the solutions of the corresponding skeleton equations simply replacing the noise by the elements of the Cameron-Martin space. It turns out that the correct rate function for MVSDEs i…
Derivative estimates for SDEs with singular and unbounded coefficients
本文提出统一的PDE-概率框架，用于估计与具有奇异和无界系数的随机微分方程相关马尔可夫半群的点wise梯度和Hessian估计，通过局部结构假设和积分正则性条件，获得短时正则化估计和长时衰减界。
Under a Lipschitz condition on distribution dependent coefficients, the central limit theorem and the moderate deviation principle are obtained for solutions of McKean-Vlasov type stochastic differential equations, which extend from the corresponding results for classical stochastic differential equations to the distribution dependent setting.
Let $α\in(0,2)$ and $d\in{\mathbb N}$. Consider the following SDE in ${\mathbb R}^d$:$${\rm d}X_t=b(t,X_t){\rm d} t+a(t,X_{t-}){\rm d} L^{(α)}_t,\ \ X_0=x,$$where $L^{(α)}$ is a $d$-dimensional rotationally invariant $α$-stable process, $b:{\mathbb R}_+\times{\mathbb R}^d\to{\mathbb R}^d$ and $a:{\mathbb R}_+\times{\mathbb R}^d\to{\mathbb R}^d\otimes{\mathbb R}^d$ are H{ö}lder continuous functions in space, with respective order $β,γ\in (0,1)$ such that $(β\wedge γ)+α>1$, uniformly in $t$. Here $b$ may be unbounded.When $a$ is bounded and uniformly elliptic, we show that the unique solution $X…
Localized sufficient conditions for the large deviation principle of the given stochastic differential equations will be presented for stochastic differential equations with non-Lipschitzian and time-inhomogeneous coefficients, which is weaker than those relevant conditions existing in the literature. We consider at first the large deviation principle when $\int_0^t\sup_{x\in\mathbb{R}^d}||σ(s,x)||\vee|b(s,x)|ds=:C_t<\infty$ for any fixed $t$, then we generalize the conclusion to unbounded case by using bounded approximation program.
We prove the existence of weak solutions to McKean-Vlasov SDEs defined on a domain $D \subseteq \mathbb{R}^d$ with continuous and unbounded coefficients that satisfy Lyapunov type conditions, where the Lyapunov function may depend on measure. We propose a new type of {\em integrated} Lyapunov condition, where the inequality is only required to hold when integrated against the measure on which the Lyapunov function depends , and we show that this is sufficient for the existence of weak solutions to McKean-Vlasov SDEs defined on $D$. The main tool used in the proofs is the concept of a measure d…
Multi-Scale McKean-Vlasov SDEs: Moderate Deviation Principle in Different Regimes
本文研究多尺度McKean-Vlasov随机微分方程在不同时间尺度分离机制下的中度偏差原理，发现快分量噪声对速率函数有显著影响，并给出显式速率函数公式。
In Stein's method, the exchangeable pair approach is commonly used to estimate the approximation errors in normal approximation. In this paper, we establish a Cramér-type moderate deviation theorem of normal approximation for unbounded exchangeable pairs. As applications, Cramér-type moderate deviation theorems for the sums of local statistics and general Curie--Weiss model are obtained.
Malliavian differentiablity and smoothness of density for SDES with locally Lipschitz coefficients
本文研究了具有超线性增长漂移的随机微分方程解的Malliavin可微性，证明了在单调多项式增长漂移条件下的任意阶可微性，并在Hörmander假设下证明了密度的无限次可微性。
On numerical density approximations of solutions of SDEs with unbounded coefficients
本文研究了计算随机微分方程解概率密度函数的数值方法，分析了其在无界系数系统中的稳定性、一致性和收敛性，并建立了与Fokker-Planck-Kolmogorov方程的新的well-posedness和半群生成结果。
In this paper, we are concerned with convergence rate of Euler-Maruyama scheme for stochastic differential equations with rough coefficients. The key contributions lie in (i), by means of regularity of non-degenerate Kolmogrov equation, we investigate convergence rate of Euler-Maruyama scheme for a class of stochastic differential equations, which allow the drifts to be Dini-continuous and unbounded; (ii) by the aid of regularization properties of degenerate Kolmogrov equation, we discuss convergence rate of Euler-Maruyama scheme for a range of degenerate stochastic differential equations, whe…
In this paper, we study small-time asymptotic behaviors for a class of distribution dependent stochastic differential equations driven by fractional Brownian motions with Hurst parameter $H\in(1/2,1)$ and magnitude $\ep^H$. By building up a variational framework and two weak convergence criteria in the factional Brownian motion setting, we establish the large and moderate deviation principles for this type equations. Besides, we also obtain the central limit theorem, in which the limit process solves a linear equation involving the Lions derivative of the drift coefficient.
In this paper we study general nonlinear stochastic differential equations, where the usual Brownian motion is replaced by a Lévy process. We also suppose that the coefficient multiplying the increments of this process is merely Lipschitz continuous and not necessarily linear in the time-marginals of the solution as is the case in the classical McKean-Vlasov model. We first study existence, uniqueness and particle approximations for these stochastic differential equations. When the driving process is a pure jump Lévy process with a smooth but unbounded Lévy measure, we develop a stochastic cal…
Uniqueness in law for singular degenerate SDEs with respect to a (sub-)invariant measure
本文研究了一类奇异退化随机微分方程在给定(sub-)不变测度下的弱存在性和在律唯一性，通过连续马尔可夫过程子类的L^1(ℝ^d,widehatμ)唯一性获得在律唯一性，利用鞅问题证明弱存在性。
In this paper, we prove a central limit theorem and establish a moderate deviation principle for 2D stochastic hydrodynamical type systems with multiplicative noise in unbounded domains, which covers 2D Navier-Stokes equations, 2D MHD models and the 2D magnetic B?enard problem and also shell models of turbulence. The weak convergence method plays an important role in obtaining the moderate deviation principle.
We prove the well-posedness of some non-linear stochastic differential equations in the sense of McKean-Vlasov driven by non-degenerate symmetric $α$-stable Lévy processes with values in $R^d$ under some mild H{ö}lder regularity assumptions on the drift and diffusion coefficients with respect to both space and measure variables. The methodology developed here allows to consider unbounded drift terms even in the so-called super-critical case, i.e. when the stability index $α\in (0, 1)$. New strong well-posedness results are also derived from the previous analysis.
Quantitative approximation to density dependent SDEs driven by $α$-stable processes
本文基于中等相互作用粒子系统，利用 Duhamel 公式与鞅泛函不等式，为受 Brown 运动与 Lévy 过程驱动的密度依赖 McKean-Vlasov SDE 建立了定量逼近，推导出与噪声类型无关的精确经验测度收敛速率及弱与按轨道收敛速率。
Distribution dependent SDEs with multiplicative fractional noise
本文研究了由分数阶布朗运动与分布相依乘性噪声驱动的分布相依随机微分方程的适定性，引入概率测度路径的 Hölder 空间并结合压缩映射原理与分数阶微积分工具，进一步建立了方程的大偏差与中偏差原理。
Here we obtain the exact asymptotics for large and moderate deviations, strong law of large numbers and central limit theorem for chains with unbounded variable length memory.
The strong convergence rate of the Euler scheme for SDEs driven by additive fractional Brownian motions is studied, where the fractional Brownian motion has Hurst parameter $H\in(\frac13,\frac12)$ and the drift coefficient is not required to be bounded. The Malliavin calculus, the rough path theory and the $2$D Young integral are utilized to overcome the difficulties caused by the low regularity of the fractional Brownian motion and the unboundedness of the drift coefficient. The Euler scheme is proved to have strong order $2H$ for the case that the drift coefficient has bounded derivatives up…
General large deviations and functional iterated logarithm law for multivalued McKean-Vlasov stochastic differential equations
本文针对多值McKean-Vlasov随机微分方程，在非Lipschitz系数下利用弱收敛方法建立了一般大偏差和中偏差原理，并由此推导出解的泛函迭代对数律。
Set-Valued Stochastic Differential Equations with Unbounded Coefficients
本文聚焦于凸闭无界集空间上的集值分析，建立理论框架研究具有无界系数的集值随机微分方程，证明特定条件下消去律成立及标准技巧的有效性。
L2 convergence of smooth approximations of Stochastic Differential Equations with unbounded coefficients
本文针对具有无界系数的随机微分方程，结合传统随机分析与粗糙路径技术证明了其分段线性Wong-Zakai逼近的L^2收敛性，弥补了现有结果仅覆盖几乎必然收敛的不足。
Singular Backward SDEs for Optimal Control with State Constraints
研究一类由鞅被积项非线性依赖导致爆炸的奇异BSDE，构造极小解并给出爆炸估计，应用于带状态约束的无限时域随机最优控制，建立验证定理并联系粘性Hamilton-Jacobi方程大解。
Optimal control of stochastic Volterra integral equations with completely monotone kernels and stochastic differential equations on Hilbert spaces with unbounded control and diffusion operators
本文研究了具有完全单调核的随机Volterra积分方程的最优控制问题，通过马尔可夫提升方法将其转化为Hilbert空间上的随机微分方程问题，并证明了新的平滑性质，从而建立了Hamilton-Jacobi-Bellman方程的弱解存在性和唯一性，以及构造了最优反馈控制。
Moderate deviation principles for stochastic 2D hydrodynamics-type systems with multiplicative jump noise
本文针对乘性跳噪声驱动的随机二维流体动力学型系统，在不要求Gelfand三元组嵌入紧性的条件下，通过有限维投影与分部积分证明其满足中偏差原理，且避免了非紧情形下的时间离散化与复杂跳估计。
Ergodic Properties of Non-Linear Density-Dependent Perturbations of the Ornstein-Uhlenbeck Process
研究具有密度依赖空间无界漂移的McKean-Vlasov SDE，建立强适定性、最优高斯点态界，给出平稳密度显式表达式并证明对数Sobolev和Poincaré不等式，最后证明χ²度量下的指数收敛。
Cholesky decomposition and well-posedness of Cauchy problem for Fokker-Planck equations with unbounded coefficients
本文利用叠加原理和 Cholesky 分解算法，在低正则性和无界系数条件下证明了 Fokker-Planck 方程 Cauchy 问题的适定性，并基于次马尔可夫半群理论确立了解的存在性与遍历性。
First, under a geometric ergodicity assumption, we provide some limit theorems and some probability inequalities for the bifurcating Markov chains (BMC). The BMC model was introduced by Guyon to detect cellular aging from cell lineage, and our aim is thus to complete his asymptotic results. The deviation inequalities are then applied to derive first result on the moderate deviation principle (MDP) for a functional of the BMC with a restricted range of speed, but with a function which can be unbounded. Next, under a uniform geometric ergodicity assumption, we provide deviation inequalities for …
We consider a stable but nearly unstable autoregressive process of any order. The bridge between stability and instability is expressed by a time-varying companion matrix $A_{n}$ with spectral radius $ρ(A_{n}) < 1$ satisfying $ρ(A_{n}) \rightarrow 1$. In that framework, we establish a moderate deviation principle for the empirical covariance only relying on the elements of $A_{n}$ through $1-ρ(A_{n})$ and, as a by-product, we establish a moderate deviation principle for the OLS estimator when $Γ$, the renormalized asymptotic variance of the process, is invertible. Finally, when $Γ$ is singular…
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance
本文在光滑协方差且不假设高斯性的条件下，将在线最小二乘 SGD 视为相互作用粒子系统，建立其高维标度极限与涨落，揭示迭代随噪声方差从弹道、扩散到纯随机的三阶段相变，并刻画低噪声下的无穷维 SDE 涨落及极限方程解的存在唯一性。
Concentration analysis of multivariate elliptic diffusion processes
本文证明了多元不可逆扩散过程无界函数加性泛函的集中度不等式与PAC界，并应用于验证Lasso估计的约束特征值条件及分析未调整Langevin MCMC算法的采样估计。
Improved sampling algorithms and functional inequalities for non-log-concave distributions
本文改进了非对数凹分布采样算法，通过加强假设获得更优的查询复杂度和Poincaré常数界。
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