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Related papers: Slow motion for the 1D Swift-Hohenberg equation

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In optimization the duality gap between the primal and the dual problems is a measure of the suboptimality of any primal-dual point. In classical mechanics the equations of motion of a system can be derived from the Hamiltonian function,…

Optimization and Control · Mathematics 2019-11-19 Brendan O'Donoghue , Chris J. Maddison

We prove that an implicit time Euler scheme for the 2D-Boussinesq model on the torus $D$ converges. Various moment of the $W^{1,2}$-norms of the velocity and temperature, as well as their discretizations, are computed. We obtain the optimal…

Probability · Mathematics 2022-11-21 Hakima Bessaih , Annie Millet

We establish sharp stability results for of non--selfadjoint the ascent and descent spectra under strong resolvent convergence (SRS), a natural framework for finite element approximations of non-selfadjoint and singularly perturbed…

Numerical Analysis · Mathematics 2025-11-27 Marwa Ennaceur

The asymptotic behavior of a class of stochastic reaction-diffusion-advection equations in the plane is studied. We show that as the divergence-free advection term becomes larger and larger, the solutions of such equations converge to the…

Probability · Mathematics 2020-08-10 Sandra Cerrai , Guangyu Xi

In this article, we are concerned with long-time behaviour of solutions to a semi-classical Schr\"odinger-type equation on the torus. We consider time scales which go to infinity when the semi-classical parameter goes to zero and we…

Analysis of PDEs · Mathematics 2012-11-08 Nalini Anantharaman , Clotilde Fermanian-Kammerer , Fabricio Macià

We quantize a multidimensional $SDE$ (in the Stratonovich sense) by solving the related system of $ODE$'s in which the $d$-dimensional Brownian motion has been replaced by the components of functional stationary quantizers. We make a…

Probability · Mathematics 2013-04-03 Gilles Pagès , Afef Sellami

We propose a novel second-order ODE as the continuous-time limit of a Riemannian accelerated gradient-based method on a manifold with curvature bounded from below. This ODE can be seen as a generalization of the ODE derived for Euclidean…

Optimization and Control · Mathematics 2020-03-10 Foivos Alimisis , Antonio Orvieto , Gary Bécigneul , Aurelien Lucchi

We consider the Carleson's problem regarding small time almost everywhere convergence to initial data for the Schr\"odinger equation, both linear and nonlinear on $\mathbb{R}$. It is shown, via the smoothing effect of the Schr\"odinger…

Analysis of PDEs · Mathematics 2026-02-23 Brian Choi

A jumping process, defined in terms of jump size distribution and waiting time distribution, is presented. The jumping rate depends on the process value. The process, which is Markovian and stationary, relaxes to an equilibrium and is…

Statistical Mechanics · Physics 2015-07-20 T. Srokowski , A. Kaminska

We present the microbalance including the microforces, the first- and second-order microstresses for the Swift--Hohenberg equation concomitantly with their constitutive equations, which are consistent with the free-energy imbalance. We…

Fluid Dynamics · Physics 2017-06-28 LFR Espath , AF Sarmiento , L Dalcin , VM Calo

We study the strong approximation of the solutions to singular stochastic kinetic equations (also referred to as second-order SDEs) driven by $\alpha$-stable processes, using an Euler-type scheme inspired by [11]. For these equations, the…

Probability · Mathematics 2025-11-18 Chengcheng Ling

We prove that the mild solution to a semilinear stochastic evolution equation on a Hilbert space, driven by either a square integrable martingale or a Poisson random measure, is (jointly) continuous, in a suitable topology, with respect to…

Analysis of PDEs · Mathematics 2012-05-29 Carlo Marinelli , Luca Di Persio , Giacomo Ziglio

We investigate stationary solutions of a thin-film model for liquid two-layer flows in an energetic formulation that is motivated by its gradient flow structure. The goal is to achieve a rigorous understanding of the contact-angle…

Analysis of PDEs · Mathematics 2012-10-23 Sebastian Jachalski , Robert Huth , Georgy Kitavtsev , Dirk Peschka , Barbara Wagner

By means of an original approach, called "method of the moving frame", we establish existence, uniqueness and stability results for mild and weak solutions of stochastic partial differential equations (SPDEs) with path dependent…

Probability · Mathematics 2010-01-18 Damir Filipovic , Stefan Tappe , Josef Teichmann

Stochastic gradient descent (SGD) is a simple and popular method to solve stochastic optimization problems which arise in machine learning. For strongly convex problems, its convergence rate was known to be O(\log(T)/T), by running SGD for…

Machine Learning · Computer Science 2015-03-19 Alexander Rakhlin , Ohad Shamir , Karthik Sridharan

Non-local reaction-diffusion partial differential equations (PDEs) involving the fractional Laplacian have arisen in a wide variety of applications. One common tool to analyse the dynamics of classical local PDEs near instability is to…

Analysis of PDEs · Mathematics 2024-03-06 Christian Kuehn , Sebastian Throm

In this note, we show two results in the setting of Galdi-Silvestre strong solutions for the rigid body-viscous fluid interaction. The former, under an additional integrability assumption on the gradient of the initial data, proves that the…

Analysis of PDEs · Mathematics 2025-08-07 Paolo Maremonti , Filippo Palma

We consider two problems arising in the study of the Schr\"odinger-Newton equations. The first is to find their Lie point symmetries. The second, as an application of the first, is to investigate an approximate solution corresponding to…

Mathematical Physics · Physics 2009-11-11 Oliver Robertshaw , Paul Tod

We are interested in the gradient flow of a general first order convex functional with respect to the $L^1$-topology. By means of an implicit minimization scheme, we show existence of a global limit solution, which satisfies an…

Analysis of PDEs · Mathematics 2023-10-13 Antonin Chambolle , Matteo Novaga

We consider the following second-order stochastic differential equation on $\mathbb{R}^{2d}$: \begin{equation*} dX_t^m=Y_t^mdt, \quad mdY_t^m=b(X_t^m)dt+\sigma(X_t^m)dB_t-Y^m_tdt, \end{equation*} where $X^m_t$ and $Y^m_t$ represent the…

Probability · Mathematics 2026-02-03 Shiyu Liu , Wei Liu , Lihu Xu