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This article is a sequel to [M.Z.Z.1] aimed at completing the characterization of the pathwise local structure of solutions of semilinear stochastic evolution equations (see's) and stochastic partial differential equations (spde's) near…

Probability · Mathematics 2008-09-19 Salah-Eldin A. Mohammed , Tusheng Zhang , Huaizhong Zhao

A new class of fractional-order stochastic evolution equations of the form $(\partial_t + A)^\gamma X(t) = \dot{W}^Q(t)$, $t\in[0,T]$, $\gamma \in (0,\infty)$, is introduced, where $-A$ generates a $C_0$-semigroup on a separable Hilbert…

Probability · Mathematics 2026-01-06 Kristin Kirchner , Joshua Willems

We consider the Cauchy problem for a linear stochastic partial differential equation. By extending the parametrix method for PDEs whose coefficients are only measurable with respect to the time variable, we prove existence, regularity in…

Probability · Mathematics 2019-12-13 Andrea Pascucci , Antonello Pesce

In the analysis of PDEs, regularity of often measured in terms of Sobolev, H{\"o}lder, Besov or Lipschitz spaces, etc. However, sometimes a gain of regularity can also be expressed just in terms of Lebesgue spaces, by passing from a…

Analysis of PDEs · Mathematics 2022-06-02 Diego Chamorro , David Llerena

Many systems in physics, engineering, and biology exhibit multiscale stochastic dynamics, where low-dimensional slow variables evolve under the influence of high-dimensional fast processes. In practice, observations are often limited to a…

Machine Learning · Statistics 2026-05-12 Anan Saha , Arnab Ganguly

The main objective of this work is to characterize the pathwise local structure of solutions of semilinear stochastic evolution equations (see's) and stochastic partial differential equations (spde's) near stationary solutions. Such…

Probability · Mathematics 2008-09-19 Salah-Eldin A Mohammed , Tusheng Zhang , Huaizhong Zhao

In the first part of this doctoral thesis we develop a regularity theory for a polyconvex functional in compressible elasticity. In the second part, we will concentrate on uniqueness questions in various situations of finite elasticity.…

Analysis of PDEs · Mathematics 2022-10-27 Marcel Dengler

A challenge in multivariate problems with discrete structures is the inclusion of prior information that may differ in each separate structure. A particular example of this is seismic amplitude versus angle (AVA) inversion to elastic…

Methodology · Statistics 2012-08-09 Erlend Aune , Daniel Simpson

These lecture notes evolve around mathematical concepts arising in inverse problems. We start by introducing inverse problems through examples such as differentiation, deconvolution, computed tomography and phase retrieval. This then leads…

Numerical Analysis · Mathematics 2025-08-26 Danielle Bednarski , Tim Roith

This Ph.D. thesis is divided in two parts. The first one concerns the equilibrium properties of glassy systems. Some aspects of the phenomenology of glasses and of theories attempting to describe them are reviewed in chapter 1. A study of…

Disordered Systems and Neural Networks · Physics 2007-05-23 F. Zamponi

Lemma 4.8 in the article [Regularity structures and renormalisation of FitzHugh-Nagumo SPDEs in three space dimensions, Electronic J. Probability 21 (18):1-48 (2016), arXiv:1504.02953] contains a mistake, which implies a weaker regularity…

Probability · Mathematics 2019-10-11 Nils Berglund , Christian Kuehn

We study a class of focusing nonlinear Schroedinger-type equations derived recently by Dumas, Lannes and Szeftel within the mathematical description of high intensity laser beams [7]. These equations incorporate the possibility of a…

Analysis of PDEs · Mathematics 2019-01-21 Paolo Antonelli , Jack Arbunich , Christof Sparber

We give a systematic description of a canonical renormalisation procedure of stochastic PDEs containing nonlinearities involving generalised functions. This theory is based on the construction of a new class of regularity structures which…

Rings and Algebras · Mathematics 2018-11-20 Yvain Bruned , Martin Hairer , Lorenzo Zambotti

Partial differential equations (PDEs) govern nearly every physical process in science and engineering, yet solving them at scale remains prohibitively expensive. Generative AI has transformed language, vision, and protein science, but…

Machine Learning · Computer Science 2026-04-10 Yilong Dai , Shengyu Chen , Xiaowei Jia , Runlong Yu

The well-posedness for SDEs with singularity in both space and distribution variables is derived, where the interacting drift term is bounded and Lipschitz continuous under total variation distance and the diffusion term is allowed to be…

Probability · Mathematics 2025-07-25 Xing Huang

Rate-independent systems arise in a number of applications. Usually, weak solutions to such problems with potentially very low regularity are considered, requiring mathematical techniques capable of handling nonsmooth functions. In this…

Analysis of PDEs · Mathematics 2017-08-18 Filip Rindler , Sebastian Schwarzacher , Endre Süli

Localized patterns are coherent structures embedded in a quiescent state and occur in both discrete and continuous media across a wide range of applications. While it is well-understood how domain covering patterns (for example stripes and…

Pattern Formation and Solitons · Physics 2025-03-19 Jason J. Bramburger , Dan J. Hill , David J. B. Lloyd

The first well founded perturbation theory for classical solid systems is presented. Theoretical approaches to thermodynamic and structural properties of the hard-sphere solid provide us with the reference system. The traditional…

Condensed Matter · Physics 2009-10-28 C. Rascon , L. Mederos , G. Navascues

In a recent interesting work [15], W.Y. He established the important partial regularity theory and the almost optimal higher regularity theory for energy minimizing harmonic almost complex structures. Based on a new observation on the…

Analysis of PDEs · Mathematics 2025-12-19 Chang-Yu Guo , Ming-Lun Liu , Chang-Lin Xiang

The paper deals with non-linear Poisson neuron network models with bounded memory dynamics, that can include both Hebbian learning mechanisms and refractory periods. The state of a network is described by the times elapsed since its neurons…

Probability · Mathematics 2012-06-21 Konstantin Borovkov , Geoffrey Decrouez , Matthieu Gilson