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The purpose of the present paper is to establish moderate deviation principles for a rather general class of random variables fulfilling certain bounds of the cumulants. We apply a celebrated lemma of the theory of large deviations…

Probability · Mathematics 2012-09-28 Hanna Doering , Peter Eichelsbacher

Discretizing variational principles, as opposed to discretizing differential equations, leads to discrete-time analogues of mechanics, and, systematically, to geometric numerical integrators. The phase space of such variational…

Mathematical Physics · Physics 2015-05-13 Charles Cuell , George W. Patrick

We prove a large deviation principle for a sequence of point processes defined by Gibbs probability measures on a Polish space. This is obtained as a consequence of a more general Laplace principle for the non-normalized Gibbs measures. We…

Probability · Mathematics 2020-04-08 David García-Zelada

Mathematical mean-field approaches have been used in many fields, not only in Physics and Chemistry, but also recently in Finance, Economics, and Game Theory. In this paper we will study a new special mean-field problem in a purely…

Probability · Mathematics 2012-10-03 Juan Li

We seek to establish qualitative convergence results to a general class of evolution PDEs described by gradient flows in optimal transportation distances. These qualitative convergence results come from dynamical systems under the general…

Analysis of PDEs · Mathematics 2020-10-02 J. A. Carrillo , R. S. Gvalani , J. Wu

Stochastic symmetries and related invariance properties of finite dimensional SDEs driven by general c\`adl\`ag semimartingales taking values in Lie groups are defined and investigated. In order to enlarge the class of possible symmetries…

Probability · Mathematics 2017-08-08 Sergio Albeverio , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

We present the package SADE (Symmetry Analysis of Differential Equations) for the determination of symmetries and related properties of systems of differential equations. The main methods implemented are: Lie, nonclassical, Lie-B\"acklund…

Mathematical Physics · Physics 2015-05-18 Tarcí sio M. Rocha Filho , Annibal Figueiredo

Accurate approximation of probability measures is essential in numerical applications. This paper explores the quantization of probability measures using the maximum mean discrepancy (MMD) distance as a guiding metric. We first investigate…

Optimization and Control · Mathematics 2025-03-18 Zahra Mehraban , Alois Pichler

The estimate of coefficients of the Convection-Diffusion Equation (CDE) from experimental measurements belongs in the category of inverse problems, which are known to come with issues of ill-conditioning or singularity. Here we concentrate…

Plasma Physics · Physics 2012-12-05 F. Sattin , D. F. Escande , Y. Camenen , A. T. Salmi , T. Tala

Many partial differential equations (PDEs) such as Navier--Stokes equations in fluid mechanics, inelastic deformation in solids, and transient parabolic and hyperbolic equations do not have an exact, primal variational structure. Recently,…

Numerical Analysis · Mathematics 2025-03-04 N. Sukumar , Amit Acharya

Fourth-order accurate compact schemes for variable coefficient convection diffusion equations are considered. A sufficient condition for the stability of the fully discrete problem is derived using a difference equation based approach. The…

Numerical Analysis · Mathematics 2024-01-30 Anindya Goswami , Kuldip Singh Patel , Pradeep Kumar Sahu

Gaussian beams are asymptotically valid high frequency solutions concentrated on a single curve through the physical domain, and superposition of Gaussian beams provides a powerful tool to generate more general high frequency solutions to…

Numerical Analysis · Mathematics 2019-05-23 Hailiang Liu , James Ralston , Peimeng Yin

We collect examples of boundary-value problems of Dirichlet and Dirichlet-Neumann type which we found instructive when designing and analysing numerical methods for fully nonlinear elliptic partial differential equations. In particular, our…

Numerical Analysis · Mathematics 2018-12-18 Max Jensen , Iain Smears

We study a class of McKean--Vlasov Stochastic Differential Equations (MV-SDEs) with drifts and diffusions having super-linear growth in measure and space -- the maps have general polynomial form but also satisfy a certain monotonicity…

Probability · Mathematics 2025-02-03 Xingyuan Chen , Goncalo dos Reis , Wolfgang Stockinger

We describe and analyze some Monte Carlo methods for manifolds in Euclidean space defined by equality and inequality constraints. First, we give an MCMC sampler for probability distributions defined by un-normalized densities on such…

Numerical Analysis · Mathematics 2017-09-21 Emilio Zappa , Miranda Holmes-Cerfon , Jonathan Goodman

A geometrical formulation for adjoint-symmetries as 1-forms is studied for general partial differential equations (PDEs), which provides a dual counterpart of the geometrical meaning of symmetries as tangent vector fields on the solution…

Mathematical Physics · Physics 2021-03-23 Stephen C. Anco , Bao Wang

Our interest in this paper is a generalization of the additive Deligne-Simpson problem which is originally defined for Fuchsian differential equations on the Riemann sphere. We shall extend this problem to differential equations having an…

Classical Analysis and ODEs · Mathematics 2017-04-05 Kazuki Hiroe

Recently, various evolutionary partial differential equations (PDEs) with a mixed derivative have been emerged and drawn much attention. Nonetheless, their PDE-theoretical and numerical studies are still in their early stage. In this paper,…

Numerical Analysis · Mathematics 2017-12-12 Shun Sato , Takayasu Matsuo

Principle of Relativity involving all, not only subluminal, inertial frames leads to the disturbance of causal laws in a way known from the fundamental postulates of Quantum Theory. We show how quantum indeterminacy based on complex…

Quantum Physics · Physics 2008-07-01 Andrzej Dragan

A complete recipe of measure-preserving diffusions in Euclidean space was recently derived unifying several MCMC algorithms into a single framework. In this paper, we develop a geometric theory that improves and generalises this…

Probability · Mathematics 2021-05-07 Alessandro Barp , So Takao , Michael Betancourt , Alexis Arnaudon , Mark Girolami
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