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Efficient simulation of stochastic partial differential equations (SPDE) on general domains requires noise discretization. This paper employs piecewise linear interpolation of noise in a fully discrete finite element approximation of a…

Numerical Analysis · Mathematics 2024-10-22 Gabriel Lord , Andreas Petersson

We study the weak convergence behaviour of the Leimkuhler--Matthews method, a non-Markovian Euler-type scheme with the same computational cost as the Euler scheme, for the approximation of the stationary distribution of a one-dimensional…

Numerical Analysis · Mathematics 2025-01-14 Xingyuan Chen , Goncalo dos Reis , Wolfgang Stockinger , Zac Wilde

The main objective of this paper is to present an efficient structure-preserving scheme, which is based on the idea of the scalar auxiliary variable approach, for solving the space fractional nonlinear Schr\"{o}dinger equation. First, we…

Numerical Analysis · Mathematics 2019-11-19 Yayun Fu , Wenjun Cai , Yushun Wang

We introduce a differential structure for the space of weakly geometric p rough paths over a Banach space V for 2<p<3. We begin by considering a certain natural family of smooth rough paths and differentiating in the truncated tensor…

Probability · Mathematics 2011-03-01 Zhongmin Qian , Jan Tudor

In this paper, we study darning of general symmetric Markov processes by shorting some parts of the state space into singletons. A natural way to construct such processes is via Dirichlet forms restricted to the function space whose members…

Probability · Mathematics 2017-02-08 Zhen-Qing Chen , Jun Peng

A discrete version of the WKB method is developed and applied to calculate the tunnel splittings between classically degenerate states of spin Hamiltonians. The results for particular model problems are in complete accord with those…

Condensed Matter · Physics 2009-10-31 Anupam Garg

We consider a family of algorithms that successively sample and minimize simple stochastic models of the objective function. We show that under reasonable conditions on approximation quality and regularity of the models, any such algorithm…

Optimization and Control · Mathematics 2018-08-28 Damek Davis , Dmitriy Drusvyatskiy

We introduce a geometrically transparent strict saddle property for nonsmooth functions. This property guarantees that simple proximal algorithms on weakly convex problems converge only to local minimizers, when randomly initialized. We…

Optimization and Control · Mathematics 2021-02-18 Damek Davis , Dmitriy Drusvyatskiy

Blind deconvolution is an ill-posed problem arising in various fields ranging from microscopy to astronomy. The ill-posed nature of the problem requires adequate priors to arrive to a desirable solution. Recently, it has been shown that…

Computer Vision and Pattern Recognition · Computer Science 2021-12-21 Gustav Bredell , Ertunc Erdil , Bruno Weber , Ender Konukoglu

We propose a discrete functional analysis result suitable for proving compactness in the framework of fully discrete approximations of strongly degenerate parabolic problems. It is based on the original exploitation of a result related to…

Numerical Analysis · Mathematics 2015-04-16 Boris Andreianov , Clément Cancès , Ayman Moussa

We discuss the rigorous justification of the spatial discretization by means of Fourier spectral methods of quasilinear first-order hyperbolic systems. We provide uniform stability estimates that grant spectral convergence of the…

Numerical Analysis · Mathematics 2025-11-06 Vincent Duchêne , Johanna Ulvedal Marstrander

We prove the optimal strong convergence rate of a fully discrete scheme, based on a splitting approach, for a stochastic nonlinear Schr\"odinger (NLS) equation. The main novelty of our method lies on the uniform a priori estimate and…

Numerical Analysis · Mathematics 2019-02-25 Jianbo Cui , Jialin Hong , Zhihui Liu , Weien Zhou

Immersed boundary methods have attracted substantial interest in the last decades due to their potential for computations involving complex geometries. Often these cannot be efficiently discretized using boundary-fitted finite elements.…

Computational Engineering, Finance, and Science · Computer Science 2026-01-13 Tim Bürchner , Lars Radtke , Philipp Kopp , Stefan Kollmannsberger , Ernst Rank , Alexander Düster

The numerical solution of partial differential equations on high-dimensional domains gives rise to computationally challenging linear systems. When using standard discretization techniques, the size of the linear system grows exponentially…

Numerical Analysis · Mathematics 2015-08-13 Daniel Kressner , Michael Steinlechner , Bart Vandereycken

In this addendum we provide an existence and uniqueness result for mild solutions to semilinear stochastic partial differential equations driven by Wiener processes and Poisson random measures in the framework of the semigroup approach with…

Probability · Mathematics 2024-10-02 Stefan Tappe

Contraction properties of transport maps between probability measures play an important role in the theory of functional inequalities. The actual construction of such maps, however, is a non-trivial task and, so far, relies mostly on the…

Probability · Mathematics 2025-11-25 Dan Mikulincer , Yair Shenfeld

We compare the continuous and discrete truncated Wigner approximations of various spin models' dynamics to exact analytical and numerical solutions. We account for all components of spin-spin correlations on equal footing, facilitated by a…

Quantum Physics · Physics 2019-04-29 Bhuvanesh Sundar , Kenneth C Wang , Kaden R A Hazzard

This article presents a superconvergence for the gradient approximation of the second order elliptic equation discretized by the weak Galerkin finite element methods on nonuniform rectangular partitions. The result shows a convergence of…

Numerical Analysis · Mathematics 2018-06-21 Dan Li , Chunmei Wang , Junping Wang

We consider weak convergence of the rescaled error processes arising from Riemann discretizations of certain stochastic integrals and relate the $L_p$-integrability of the weak limit to the fractional smoothness in the Malliavin sense of…

Probability · Mathematics 2010-01-25 Stefan Geiss , Anni Toivola

Herein, a methodology is developed to replicate functions, measures and stochastic processes onto a compact metric space. Many results are easily established for the replica objects and then transferred back to the original ones. Two…

Probability · Mathematics 2020-11-03 Chi Dong , Michael A. Kouritzin