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We establish the exact quenched asymptotic growth of the solution to the parabolic Anderson model (PAM) in the hyperbolic space with a regular, stationary, time-independent Gaussian potential. More precisely, we show that with probability…

Probability · Mathematics 2026-02-03 Xi Geng , Sheng Wang , Weijun Xu

We consider the parabolic Anderson model (PAM) $\partial_t u = \frac12 \Delta u + \xi u$ in $\mathbb R^2$ with a Gaussian (space) white-noise potential $\xi$. We prove that the almost-sure large-time asymptotic behaviour of the total mass…

Probability · Mathematics 2026-05-14 Wolfgang König , Nicolas Perkowski , Willem van Zuijlen

We consider the continuous parabolic Anderson model with the Gaussian fields under the measure-valued initial conditions, the covariances of which are nonhomogeneous in time and fractional rough in space. We mainly study the spatial…

Probability · Mathematics 2021-02-02 Yangyang Lyu

We consider the solution $u\colon [0,\infty) \times\mathbb{Z}^d\rightarrow [0,\infty) $ to the parabolic Anderson model, where the potential is given by $(t,x)\mapsto\gamma\delta_{Y_t}(x)$ with $Y$ a simple symmetric random walk on…

Probability · Mathematics 2011-02-18 Adrian Schnitzler , Tilman Wolff

Let $B_s$ be a $d$-dimensional Brownian motion and $\omega(dx)$ be an independent Poisson field on $\mathbb{R}^d$. The almost sure asymptotics for the logarithmic moment generating function [\log\math…

Probability · Mathematics 2012-07-30 Xia Chen

In this paper, we introduce a natively positive approximation method based on the Feynman-Kac representation using random walks, to approximate the solution to the one-dimensional parabolic Anderson model of Skorokhod type, with either a…

Probability · Mathematics 2025-12-30 Panqiu Xia , Jiayu Zheng

In this paper we study the linear stochastic heat equation, also known as parabolic Anderson model, in multidimension driven by a Gaussian noise which is white in time and it has a correlated spatial covariance. Examples of such covariance…

Probability · Mathematics 2016-03-22 Jingyu Huang , Khoa Lê , David Nualart

We study the long-time asymptotics of the total mass of the solution to the parabolic Anderson model (PAM) on a supercritical Galton-Watson random tree with bounded degrees. We identify the second-order contribution to this asymptotics in…

Probability · Mathematics 2020-07-29 Frank den Hollander , Wolfgang König , Renato S. dos Santos

This paper studies the one-dimensional parabolic Anderson model driven by a Gaussian noise which is white in time and has the covariance of a fractional Brownian motion with Hurst parameter $H \in (\frac{1}{4}, \frac{1}{2})$ in the space…

Probability · Mathematics 2016-12-21 Yaozhong Hu , Jingyu Huang , Khoa Lê , David Nualart , Samy Tindel

In this note, we use the Feynman-Kac formula to derive a moment representation for the 2D parabolic Anderson model in small time, which is related to the intersection local time of planar Brownian motions.

Probability · Mathematics 2017-11-22 Yu Gu , Weijun Xu

We consider the linear stochastic heat equation on $\mathbb{R}^\ell$, driven by a Gaussian noise which is colored in time and space. The spatial covariance satisfies general assumptions and includes examples such as the Riesz kernel in any…

Probability · Mathematics 2017-04-28 Jingyu Huang , Khoa Lê , David Nualart

Consider a Parabolic Anderson model (PAM) with Gaussian noise that is white in time and colored in space, where the spatial correlation decays polynomially with order $\alpha$. In Euclidean spaces with dimension greater than $2$, it is…

Probability · Mathematics 2025-07-09 Xi Geng , Cheng Ouyang

We consider the parabolic Anderson model (PAM) which is given by the equation $\partial u/\partial t = \kappa\Delta u + \xi u$ with $u\colon\, \Z^d\times [0,\infty)\to \R$, where $\kappa \in [0,\infty)$ is the diffusion constant, $\Delta$…

Probability · Mathematics 2011-03-24 Fabienne Castell , Onur Gün , Grégory Maillard

This article resumes the analysis of precise Laplace asymptotics for the generalised Parabolic Anderson Model (gPAM) initiated by Peter Friz and the author. More precisely, we provide an explicit formula for the constant coefficient in the…

Probability · Mathematics 2024-12-04 Tom Klose

Partially motivated by the recent papers of Conus, Joseph and Khoshnevisan [Ann. Probab. 41 (2013) 2225-2260] and Conus et al. [Probab. Theory Related Fields 156 (2013) 483-533], this work is concerned with the precise spatial asymptotic…

Probability · Mathematics 2016-03-31 Xia Chen

This study proposes a detailed nonlinear mathematical model of an antagonistic pneumatic artificial muscle (PAM) actuator system for estimating the joint angle and torque using an unscented Kalman filter (UKF). The proposed model is…

Systems and Control · Electrical Eng. & Systems 2021-06-08 Takaya Shin , Takumi Ibayashi , Kiminao Kogiso

Let $\xi$ be a Gaussian white noise on $\mathbb R^d$ ($d=1,2,3$). Let $(\xi_\varepsilon)_{\varepsilon>0}$ be continuous Gaussian processes such that $\xi_\varepsilon\to\xi$ as $\varepsilon\to0$, defined by convolving $\xi$ against a…

Probability · Mathematics 2021-05-26 Pierre Yves Gaudreau Lamarre

We derive exact asymptotics of time correlation functions for the parabolic Anderson model with homogeneous initial condition and time-independent tails that decay more slowly than those of a double exponential distribution and have a…

Probability · Mathematics 2011-11-01 Jürgen Gärtner , Adrian Schnitzler

We consider the class of all stationary Gaussian process with explicit parametric spectral density. Under some conditions on the autocovariance function, we defined a GMM estimator that satisfies consistency and asymptotic normality, using…

Statistics Theory · Mathematics 2017-01-18 Luis A. Barboza , Frederi G. Viens

We consider the Feynman-Kac functional associated with a Brownian motion in a random potential. The potential is defined by attaching a heavy tailed positive potential around the Poisson point process. This model was first considered by…

Probability · Mathematics 2011-10-28 Ryoki Fukushima
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