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Fix a smooth Morse function $U\colon \mathbb{R}^{d}\to\mathbb{R}$ with finitely many critical points, and consider the solution of the stochastic differential equation \[ d\boldsymbol{x}_{\epsilon}(t)=-\nabla…

Probability · Mathematics 2025-09-18 Claudio Landim , Jungkyoung Lee , Mauro Mariani

The Moderate Deviations Principle (MDP) is well-understood for sums of independent random variables, worse understood for stationary random sequences, and scantily understood for random fields. Here it is established for some planary random…

Probability · Mathematics 2019-09-25 Boris Tsirelson

The paper focuses on unconditionally optimal error analysis of the fully discrete Galerkin finite element methods for a general nonlinear parabolic system in $\R^d$ with $d=2,3$. In terms of a corresponding time-discrete system of PDEs as…

Numerical Analysis · Mathematics 2013-03-27 Buyang Li , Weiwei Sun

The sample-function regularity of the random-field solution to a stochastic partial differential equation (SPDE) depends naturally on the roughness of the external noise, as well as on the properties of the underlying integro-differential…

Probability · Mathematics 2023-11-21 Davar Khoshnevisan , Marta Sanz-Solé

In this work, we investigate the numerical approximation of the second order non-autonomous semilnear parabolic partial differential equation (PDE) using the finite element method. To the best of our knowledge, only the linear case is…

Numerical Analysis · Mathematics 2020-01-27 Antoine Tambue , Jean Daniel Mukam

For parabolic stochastic partial differential equations (SPDEs), we show that the numerical methods, including the spatial spectral Galerkin method and further the full discretization via the temporal accelerated exponential Euler method,…

Numerical Analysis · Mathematics 2021-06-22 Chuchu Chen , Ziheng Chen , Jialin Hong , Diancong Jin

In this survey we review some recent rigorous results on large N problems in quantum field theory, stochastic quantization and singular stochastic PDEs, and their mean field limit problems. In particular we discuss the O(N) linear sigma…

Probability · Mathematics 2022-09-07 Hao Shen

The random connection model is a random graph whose vertices are given by the points of a Poisson process and whose edges are obtained by randomly connecting pairs of Poisson points in a position dependent but independent way. We study…

Probability · Mathematics 2018-08-06 Günter Last , Franz Nestmann , Matthias Schulte

Let $(X_i)_{i\geq 1}$ be a stationary mean-zero Gaussian process with covariances $\rho(k)=\PE(X_{1}X_{k+1})$ satisfying: $\rho(0)=1$ and $\rho(k)=k^{-D} L(k)$ where $D$ is in $(0,1)$ and $L$ is slowly varying at infinity. Consider the…

Statistics Theory · Mathematics 2010-12-08 Céline Lévy-Leduc , Hélène Boistard , Eric Moulines , Murad S. Taqqu , Valderio A. Reisen

We study the problem of list-decodable sparse mean estimation. Specifically, for a parameter $\alpha \in (0, 1/2)$, we are given $m$ points in $\mathbb{R}^n$, $\lfloor \alpha m \rfloor$ of which are i.i.d. samples from a distribution $D$…

Data Structures and Algorithms · Computer Science 2024-07-08 Ilias Diakonikolas , Daniel M. Kane , Sushrut Karmalkar , Ankit Pensia , Thanasis Pittas

Explicit, unconditionally stable, high-order schemes for the approximation of some first- andsecond-order linear, time-dependent partial differential equations (PDEs) are proposed.The schemes are based on a weak formulation of a…

Numerical Analysis · Mathematics 2017-11-15 Olivier Bokanowski , Giorevinus Simarmata

We propose a natural gradient term for a class of second-order partial differential equations of the form \begin{equation}\nonumber M(x,Du,D^2u)+g(u)N(x,Du, D^2u)+f(x,u)=0 \;\;\mbox{in}\;\; \Omega, \end{equation} where…

Analysis of PDEs · Mathematics 2026-03-18 José Francisco de Oliveira

We present a first step toward field-level cosmological inference beyond the standard $\Lambda$CDM model, focusing on optimizing precision tests in the nonlinear regime of large-scale structure (LSS). As an illustrative case, we study the…

Cosmology and Nongalactic Astrophysics · Physics 2025-06-10 Matteo Peron , Takahiro Nishimichi , Massimo Pietroni , Atsushi Taruya

The main goal of this article is to study the effect of small, highly nonlinear, unbounded drifts (small time large deviation principle (LDP) based on exponential equivalence arguments) for a class of stochastic partial differential…

Probability · Mathematics 2022-12-27 Ankit Kumar , Manil T. Mohan

Partial differential equations (PDEs) are widely used for the description of physical and engineering phenomena. Some key parameters involved in PDEs, which represent certain physical properties with important scientific interpretations,…

Numerical Analysis · Mathematics 2024-02-02 Zhaohui Li , Shihao Yang , Jeff Wu

Ordinary Differential Equations (ODEs) have recently gained a lot of attention in machine learning. However, the theoretical aspects, e.g., identifiability and asymptotic properties of statistical estimation are still obscure. This paper…

Machine Learning · Statistics 2024-06-04 Yuanyuan Wang , Wei Huang , Mingming Gong , Xi Geng , Tongliang Liu , Kun Zhang , Dacheng Tao

We are interested in (uniformly) parabolic PDEs with a nonlinear dependance of the leading-order coefficients, driven by a rough right hand side. For simplicity, we consider a space-time periodic setting with a single spatial variable:…

Analysis of PDEs · Mathematics 2018-11-07 Felix Otto , Hendrik Weber

It is well known Heyde's characterization of the Gaussian distribution on the real line: Let $\xi_1, \xi_2,\dots, \xi_n$, $n\ge 2,$ be independent random variables, let $\alpha_j, \beta_j$ be nonzero constants such that…

Probability · Mathematics 2018-11-29 Gennadiy Feldman

The problem of testing equality of the entire second order structure of two independent functional linear processes is considered. A fully functional $L^2$-type test is developed which evaluates, over all frequencies, the Hilbert-Schmidt…

Methodology · Statistics 2020-04-15 Anne Leucht , Efstathios Paparoditis , Theofanis Sapatinas

We define a new class of Gaussian processes on compact metric graphs such as street or river networks. The proposed models, the Whittle--Mat\'ern fields, are defined via a fractional stochastic differential equation on the compact metric…

Statistics Theory · Mathematics 2023-04-07 David Bolin , Alexandre B. Simas , Jonas Wallin