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Related papers: Discretisation of regularity structures

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In this paper we consider the stability and convergence of numerical discretizations of the Black-Scholes partial differential equation (PDE) when complemented with the popular linear boundary condition. This condition states that the…

Numerical Analysis · Mathematics 2015-03-20 Karel in 't Hout , Kim Volders

We investigate a discrete model consisting of self-propelled particles that obey simple interaction rules. We show that this model can self-organize and exhibit coherent localized solutions in one- and in two-dimensions.In one-dimension,…

Soft Condensed Matter · Physics 2009-10-31 Herbert Levine , Wouter-Jan Rappel , Inon Cohen

Mathematical models of biological populations commonly use discrete structure classes to capture trait variation among individuals (e.g. age, size, phenotype, intracellular state). Upscaling these discrete models into continuum descriptions…

Populations and Evolution · Quantitative Biology 2026-03-18 Eleonora Agostinelli , Keith L. Chambers , Helen M. Byrne , Mohit P. Dalwadi

We investigate the properties of discretizations of advection equations on non-cartesian grids and graphs in general. Advection equations discretized on non-cartesian grids have remained a long-standing challenge as the structure of the…

Analysis of PDEs · Mathematics 2022-11-14 Pierre-Emmanuel Jabin , Datong Zhou

We identify fundamental issues with discretization when estimating information-theoretic quantities in the analysis of data. These difficulties are theoretical in nature and arise with discrete datasets carrying significant implications for…

Quantitative Methods · Quantitative Biology 2014-06-24 Venkateshan Kannan , Jesper Tegnèr

The aim of this note is to present some recent results on the structure of the singular part of measures satisfying a PDE constraint and to describe some applications.

Analysis of PDEs · Mathematics 2017-12-27 Guido De Philippis , Filip Rindler

Discretizations of Langevin diffusions provide a powerful method for sampling and Bayesian inference. However, such discretizations require evaluation of the gradient of the potential function. In several real-world scenarios, obtaining…

Statistics Theory · Mathematics 2021-01-19 Abhishek Roy , Lingqing Shen , Krishnakumar Balasubramanian , Saeed Ghadimi

We derive a compatible discretization method that relies heavily on the underlying geometric structure, and obeys the topological sequences and commuting properties that are constructed. As a sample problem we consider the…

Mathematical Physics · Physics 2013-04-29 Jasper Kreeft , Marc Gerritsma

The aim of this paper is to present the application of an approach to study contraction theory recently developed for piecewise smooth and switched systems. The approach that can be used to analyze incremental stability properties of…

Systems and Control · Computer Science 2020-03-18 Davide Fiore , Marco Coraggio , Mario di Bernardo

As the main contribution, this document provides a consistent discretization of a class of fixed-time stable systems, namely predefined-time stable systems. In the unperturbed case, the proposed approach allows obtaining not only a…

Analyzing and controlling system entropy is a powerful tool for regulating predictability of control systems. Applications benefiting from such approaches range from reinforcement learning and data security to human-robot collaboration. In…

Systems and Control · Electrical Eng. & Systems 2026-03-06 Menno van Zutphen , Giannis Delimpaltadakis , Duarte J. Antunes

Solutions of partial differential equations (PDEs) on manifolds have provided important applications in different fields in science and engineering. Existing methods are majorly based on discretization of manifolds as implicit functions,…

Numerical Analysis · Mathematics 2017-08-03 Rongjie Lai , Jia Li

Numerical models based on partial differential equations (PDE), or integro-differential equations, are ubiquitous in engineering and science, making it possible to understand or design systems for which physical experiments would be…

Computational Physics · Physics 2021-04-02 Julien Bect , Souleymane Zio , Guillaume Perrin , Claire Cannamela , Emmanuel Vazquez

The method of regularised stokeslets is widely used in microscale biological fluid dynamics due to its ease of implementation, natural treatment of complex moving geometries, and removal of singular functions to integrate. The standard…

Numerical Analysis · Mathematics 2021-03-10 Meurig Gallagher , David Smith

A new notion of stochastic transformation is proposed and applied to the study of both weak and strong symmetries of stochastic differential equations (SDEs). The correspondence between an algebra of weak symmetries for a given SDE and an…

Probability · Mathematics 2016-08-02 Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

The use of discrete material representation in numerical models is advantageous due to the straightforward way it takes into account material heterogeneity and randomness, and the discrete and orientated nature of cracks. Unfortunately, it…

Computational Engineering, Finance, and Science · Computer Science 2023-06-29 Jan Eliáš

This paper aims to investigate the numerical approximation of a general second order parabolic stochastic partial differential equation(SPDE) driven by multiplicative and additive noise. Our main interest is on such SPDEs where the…

Numerical Analysis · Mathematics 2020-11-19 Jean Daniel Mukam , Antoine Tambue

Discrete scale invariance, which corresponds to a partial breaking of the scaling symmetry, is reflected in the existence of a hierarchy of characteristic scales l0, c l0, c^2 l0,... where c is a preferred scaling ratio and l0 a microscopic…

Statistical Mechanics · Physics 2015-06-25 A. Johansen , D. Sornette

Motivated by recent applications in rough volatility and regularity structures, notably the notion of singular modelled distribution, we study paths, rough paths and related objects with a quantified singularity at zero. In a pure path…

Probability · Mathematics 2024-03-13 Carlo Bellingeri , Peter K. Friz , Máté Gerencsér

Sparsity plays a central role in recent developments in signal processing, linear algebra, statistics, optimization, and other fields. In these developments, sparsity is promoted through the addition of an $L^1$ norm (or related quantity)…

Analysis of PDEs · Mathematics 2014-08-04 Russel E. Caflisch , Stanley J. Osher , Hayden Schaeffer , Giang Tran
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