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Our focus is on the stable approximate solution of linear operator equations based on noisy data by using $\ell^1$-regularization as a sparsity-enforcing version of Tikhonov regularization. We summarize recent results on situations where…

Functional Analysis · Mathematics 2017-11-27 Daniel Gerth , Bernd Hofmann

Analytic smooth solutions of a general, strongly parabolic semi-linear Cauchy problem of $2m$-th order in $\mathbb{R}^N\times (0,T)$ with analytic coefficients (in space and time variables) and analytic initial data (in space variables) are…

Analysis of PDEs · Mathematics 2021-01-05 Falko Baustian , Peter Takáč

We study the invariant measure of the one-dimensional stochastic Allen-Cahn equation for a small noise strength and a large but finite system. We endow the system with inhomogeneous Dirichlet boundary conditions that enforce at least one…

Probability · Mathematics 2016-06-02 Felix Otto , Hendrik Weber , Maria Westdickenberg

We introduce a new family of refined Sobolev-Malliavin spaces that capture the integrability in time of the Malliavin derivative. We consider duality in these spaces and derive a Burkholder type inequality in a dual norm. The theory we…

Probability · Mathematics 2016-02-23 Adam Andersson , Raphael Kruse , Stig Larsson

We consider linear stochastic differential-algebraic equations with constant coefficients and additive white noise. Due to the nature of this class of equations, the solution must be defined as a generalised process (in the sense of Dawson…

Probability · Mathematics 2007-05-23 Aureli Alabert , Marco Ferrante

We investigate a mixed finite element method for the spatial discretization of a time-fractional Allen--Cahn equation defined on a convex polyhedral domain, combined with a nonuniform Alikhanov scheme for the temporal approximation. Under…

Numerical Analysis · Mathematics 2026-03-13 Abhinav Jha , Samir Karaa , Aditi Tomar

We consider the free linear Schroedinger equation on a torus $\mathbb T^d$, perturbed by a Hamiltonian nonlinearity, driven by a random force and damped by a linear damping: $$u_t -i\Delta u +i\nu \rho |u|^{2q_*}u = - \nu f(-\Delta) u +…

Mathematical Physics · Physics 2013-12-02 Sergei Kuksin , Alberto Maiocchi

This paper proposes and analyzes a novel fully discrete finite element scheme with the interpolation operator for stochastic Cahn-Hilliard equations with functional-type noise. The nonlinear term satisfies a one-side Lipschitz condition and…

Numerical Analysis · Mathematics 2023-06-27 Yukun Li , Corey Prachniak , Yi Zhang

We consider the stochastic Cahn-Hilliard equation with additive space-time white noise $\epsilon^{\gamma}\dot{W}$ in dimension $d=2,3$, where $\epsilon>0$ is an interfacial width parameter. We study numerical approximation of the equation…

Numerical Analysis · Mathematics 2025-01-09 Ľubomír Baňas , Jean Daniel Mukam

We study weighted Tikhonov regularization for large-scale linear discrete ill-posed problems with random noise. Under a polynomial upper-bound assumption on the generalized eigenvalues of the discrete forward operator, we derive stochastic…

Numerical Analysis · Mathematics 2026-05-19 Duan-Peng Ling , Wenlong Zhang

In this article, we study the stochastic wave equation on the entire space $\mathbb{R}^d$, driven by a space-time L\'evy white noise with possibly infinite variance (such as the $\alpha$-stable L\'evy noise). In this equation, the noise is…

Probability · Mathematics 2023-03-23 Raluca M. Balan

We give sharp regularity results for the solution to the stochastic wave equation with linear fractional-colored noise. We apply these results in order to establish upper and lower bound for the hitting probabilities of the solution in…

Probability · Mathematics 2012-03-20 Jorge Clarke De La Cerda , Ciprian Tudor

We provide a deterministic algorithm that finds, in $\epsilon^{-O(1)} n^2$ time, an $\epsilon$-regular Frieze-Kannan partition of a graph on $n$ vertices. The algorithm outputs an approximation of a given graph as a weighted sum of…

Combinatorics · Mathematics 2019-08-21 Jacob Fox , László Miklós Lovász , Yufei Zhao

This paper is the second in a series of works on weak convergence of one-step schemes for solving stochastic differential equations (SDEs) with one-sided Lipschitz conditions. It is known that the super-linear coefficients may lead to a…

Numerical Analysis · Mathematics 2024-10-29 Yuying Zhao , Xiaojie Wang , Zhongqiang Zhang

In this work, we consider a time-fractional Allen-Cahn equation, where the conventional first order time derivative is replaced by a Caputo fractional derivative with order $\alpha\in(0,1)$. First, the well-posedness and (limited) smoothing…

Numerical Analysis · Mathematics 2019-06-18 Qiang Du , Jiang Yang , Zhi Zhou

We consider a fully discrete scheme for nonlinear stochastic partial differential equations with non-globally Lipschitz coefficients driven by multiplicative noise in a multi-dimensional setting. Our method uses a polynomial based spectral…

Numerical Analysis · Mathematics 2021-12-23 Can Huang , Jie Shen

In this paper, we study the existence of random periodic solutions for semilinear stochastic partial differential equations with multiplicative linear noise on a bounded open domain ${\cal O}\subset {\mathbb R}^d$ with smooth boundary. We…

Probability · Mathematics 2018-03-02 Chunrong Feng , Yue Wu , Huaizhong Zhao

We study the compact support property for solutions of the following stochastic partial differential equations: $$\partial_t u = a^{ij}u_{x^ix^j}(t,x)+b^{i}u_{x^i}(t,x)+cu+h(t,x,u(t,x))\dot{F}(t,x),\quad (t,x)\in…

Probability · Mathematics 2023-03-07 Beom-Seok Han , Kunwoo Kim , Jaeyun Yi

We prove unique continuation properties for linear variable coefficient Schr\"odinger equations with bounded real potentials. Under certain smallness conditions on the leading coefficients, we prove that solutions decaying faster than any…

Analysis of PDEs · Mathematics 2025-01-27 Serena Federico , Zongyuan Li , Xueying Yu

Although stochastic optimization is central to modern machine learning, the precise mechanisms underlying its success, and in particular, the precise role of the stochasticity, still remain unclear. Modelling stochastic optimization…

Machine Learning · Statistics 2020-06-12 Liam Hodgkinson , Michael W. Mahoney
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