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We establish the large deviations principle (LDP) and the moderate deviations principle (MDP) and an almost sure version of the central limit theorem (CLT) for the stochastic 3D viscous primitive equations driven by a multiplicative white…

Probability · Mathematics 2020-10-27 Jakub Slavík

In this work, we propose a mixed finite element method for solving elliptic multiscale problems based on a localized orthogonal decomposition (LOD) of Raviart-Thomas finite element spaces. It requires to solve local problems in small…

Numerical Analysis · Mathematics 2016-06-21 Fredrik Hellman , Patrick Henning , Axel Målqvist

To obtain explicit understanding of the behavior of dynamical systems, geometrical methods and slow-fast analysis have proved to be highly useful. Such methods are standard for smooth dynamical systems, and increasingly used for continuous,…

Quantitative Methods · Quantitative Biology 2023-10-19 Francesco Montefusco , Morten Gram Pedersen

In [Han \& Schied, 2023, \textit{arXiv 2307.02582}], an easily computable scale-invariant estimator $\widehat{\mathscr{R}}^s_n$ was constructed to estimate the Hurst parameter of the drifted fractional Brownian motion $X$ from its…

Statistical Finance · Quantitative Finance 2025-09-09 Xiyue Han , Alexander Schied

High-dimensional Kronecker-structured estimation faces a conflict between non-convex scaling ambiguities and statistical robustness. The arbitrary factor scaling distorts gradient magnitudes, rendering standard fixed-threshold robust…

Methodology · Statistics 2025-12-23 Xiaoyu Zhang , Zhiyun Fan , Wenyang Zhang , Di Wang

We propose a multiscale method for elliptic problems on complex domains, e.g. domains with cracks or complicated boundary. For local singularities this paper also offers a discrete alternative to enrichment techniques such as XFEM. We…

Numerical Analysis · Mathematics 2016-11-01 Daniel Elfverson , Mats G. Larson , Axel Målqvist

In this article, we consider the so-called modified Euler scheme for stochastic differential equations (SDEs) driven by fractional Brownian motions (fBm) with Hurst parameter $\frac13<H<\frac12$. This is a first-order time-discrete…

Probability · Mathematics 2017-03-13 Yanghui Liu , Samy Tindel

This paper develops an It\^o-type fractional pathwise integration theory for fractional Brownian motion with Hurst parameters \( H \in (\frac{1}{3}, \frac{1}{2}] \), using the Lyons' rough path framework. This approach is designed to fill…

Probability · Mathematics 2025-11-10 Zhongmin Qian , Xingcheng Xu

The incidence of rare events in fast-slow systems is investigated via analysis of the large deviation principle (LDP) that characterizes the likelihood and pathway of large fluctuations of the slow variables away from their mean behavior --…

Statistical Mechanics · Physics 2016-02-17 Freddy Bouchet , Tobias Grafke , Tomás Tangarife , Eric Vanden-Eijnden

This article establishes cutoff convergence or abrupt convergence of three statistical quantities for multivariate (Hurwitz) stable geometric Brownian motion: the autocorrelation function, the Wasserstein distance between the current state…

Probability · Mathematics 2025-06-30 G. Barrera , M. A. Högele , J. C. Pardo

We study robust nonlinear filtering for stochastic models driven by L\'evy processes, where the signal and observation processes are coupled through common Brownian and jump noise. Robustness, defined as the continuous dependence of the…

Probability · Mathematics 2026-04-30 Sharan Srinivasan , Vijay Gupta , Harsha Honnappa

Finding a reduction of complex, high-dimensional dynamics to its essential, low-dimensional "heart" remains a challenging yet necessary prerequisite for designing efficient numerical approaches. Machine learning methods have the potential…

Dynamical Systems · Mathematics 2022-06-15 Przemyslaw Zielinski , Jan S. Hesthaven

The deviation principles of record numbers in random walk models have not been completely investigated, especially for the non-nearest neighbor cases. In this paper, we derive the asymptotic probabilities of large and moderate deviations…

Probability · Mathematics 2022-12-07 Yuqiang Li , Qiang Yao

In this paper, we construct and analyze a multiscale (finite element) method for parabolic problems with heterogeneous dynamic boundary conditions. As origin, we consider a reformulation of the system in order to decouple the discretization…

Numerical Analysis · Mathematics 2020-09-16 Robert Altmann , Barbara Verfürth

We consider the problem of minimizing a strongly convex smooth function where the gradients are subject to additive worst-case deterministic errors that are square-summable. We study the trade-offs between the convergence rate and…

Optimization and Control · Mathematics 2023-10-23 Mert Gurbuzbalaban

In this paper, we study large and moderate deviation principles for stochastic partial differential equations (SPDEs) on metric graphs and their associated multiscale models via the weak convergence approach, providing a refined…

Probability · Mathematics 2025-09-09 Jianbo Cui , Derui Sheng

In the setting of stochastic Volterra equations, and in particular rough volatility models, we show that conditional expectations are the unique classical solutions to path-dependent PDEs. The latter arise from the functional It\^o formula…

Probability · Mathematics 2026-05-27 Ofelia Bonesini , Antoine Jacquier , Alexandre Pannier

We consider a nearly-elastic model system with one degree of freedom. In each collision with the "wall", the system can either lose or gain a small amount of energy due to stochastic perturbation. The weak limit of the corresponding slow…

Probability · Mathematics 2012-08-31 Wenqing Hu

A geometric p-rough path can be seen to be a genuine path of finite p-variation with values in a Lie group equipped with a natural distance. The group and its distance lift (R^{d},+,0) and its Euclidean distance. This approach allows us to…

Probability · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

The multiway-cut problem is, given a weighted graph and k >= 2 terminal nodes, to find a minimum-weight set of edges whose removal separates all the terminals. The problem is NP-hard, and even NP-hard to approximate within 1+delta for some…

Data Structures and Algorithms · Computer Science 2015-06-02 David Karger , Phil Klein , Cliff Stein , Mikkel Thorup , Neal E. Young