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Related papers: A symmetry-adapted numerical scheme for SDEs

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Lie symmetry transformations that leave a differential equation invariant play a fundamental role in science and mathematics. Such Lie symmetry groups uniquely determine their Lie symmetry algebras. Exact differential elimination algorithms…

Mathematical Physics · Physics 2024-10-29 Siyuan Deng , Gregory Reid

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

We present an exposition of a method of discretizing ordinary differential equations while preserving their Lie point symmetries. This method is very general and can be applied to any ODE with a nontrivial symmetry group. The method is…

Mathematical Physics · Physics 2009-11-01 R. Rebelo , P. Winternitz

In this paper we propose a new numerical method for solving stochastic differential equations (SDEs). As an application of this method we propose an explicit numerical scheme for a super linear SDE for which the usual Euler scheme diverges.

Numerical Analysis · Mathematics 2013-03-14 Nikolaos Halidias

We introduce a new approach for designing numerical schemes for stochastic differential equations (SDEs). The approach, which we have called direction and norm decomposition method, proposes to approximate the required solution $X_t$ by…

Numerical Analysis · Mathematics 2017-02-21 C. M. Mora , H. A. Mardones , J. C. Jimenez , M. Selva , R. Biscay

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

We discuss various compatibility criteria for overdetermined systems of PDEs generalizing the approach to formal integrability via brackets of differential operators. Then we give sufficient conditions that guarantee that a PDE possessing a…

Differential Geometry · Mathematics 2012-03-06 Boris Kruglikov

A method is presented for calculating the Lie point symmetries of a scalar difference equation on a two-dimensional lattice. The symmetry transformations act on the equations and on the lattice. They take solutions into solutions and can be…

Mathematical Physics · Physics 2013-07-10 Decio Levi , Sébastien Tremblay , Pavel Winternitz

Given a stochastic differential equation (SDE) in $\mathbb{R}^n$ whose solution is constrained to lie in some manifold $M \subset \mathbb{R}^n$, we propose a class of numerical schemes for the SDE whose iterates remain close to $M$ to high…

Numerical Analysis · Mathematics 2020-09-24 John Armstrong , Tim King

In this paper, we study numerical approximations for stochastic differential equations (SDEs) that use adaptive step sizes. In particular, we consider a general setting where decisions to reduce step sizes are allowed to depend on the…

Numerical Analysis · Mathematics 2025-12-10 James Foster , Andraž Jelinčič

Symmetry preserving difference schemes approximating second and third order ordinary differential equations are presented. They have the same three or four-dimensional symmetry groups as the original differential equations. The new…

Mathematical Physics · Physics 2009-11-11 A. Bourlioux , C Cyr-Gagnon , P Winternitz

In this article, we introduce the concept of admitted Lie group of transformations for both backward stochastic differential equations (BSDEs) and forward backward stochastic differential equations (FBSDEs), following the approach of…

Probability · Mathematics 2025-06-13 Anas Ouknine , Paul Lescot

Lie symmetry analysis is applied to study the nonlinear rotating shallow water equations. The 9-dimensional Lie algebra of point symmetries admitted by the model is found. It is shown that the rotating shallow water equations are related…

Analysis of PDEs · Mathematics 2016-02-08 Alexander Chesnokov

We propose a novel Skew Gradient Embedding (SGE) framework for systematically reformulating thermodynamically consistent partial differential equation (PDE) models-capturing both reversible and irreversible processes-as generalized gradient…

Numerical Analysis · Mathematics 2025-09-24 Xuelong Gu , Qi Wang

We show that any first order ordinary differential equation with a known Lie point symmetry group can be discretized into a difference scheme with the same symmetry group. In general, the lattices are not regular ones, but must be adapted…

Exactly Solvable and Integrable Systems · Physics 2014-11-18 Miguel A. Rodriguez , Pavel Winternitz

We propose a geometric integrator to numerically approximate the flow of Lie systems. The key is a novel procedure that integrates the Lie system on a Lie group intrinsically associated with a Lie system on a general manifold via a Lie…

Numerical Analysis · Mathematics 2025-11-18 L. Blanco , F. Jiménez Alburquerque , J. de Lucas , C. Sardón

In this paper we propose a generalized numerical scheme for backward stochastic differential equations(BSDEs). The scheme is based on approximation of derivatives via Lagrange interpolation. By changing the distribution of sample points…

Numerical Analysis · Mathematics 2018-08-09 Chol-Kyu Pak , Mun-Chol Kim , O Hun

Ordinary differential equations (ODEs) and ordinary difference systems (O$\Delta$Ss) invariant under the actions of the Lie groups $\mathrm{SL}_x(2)$, $\mathrm{SL}_y(2)$ and $\mathrm{SL}_x(2)\times\mathrm{SL}_y(2)$ of projective…

Mathematical Physics · Physics 2016-01-20 Rutwig Campoamor-Stursberg , Miguel A. Rodríguez , Pavel Winternitz

We apply symmetry and invariance methods to analyse systems of difference equations. Non trivial symmetries are derived and their exact solutions obtained.

Dynamical Systems · Mathematics 2017-11-28 JJ Bashingwa , AH Kara , M Folly-Gbetoula

We develop the method of stochastic modified equations (SME), in which stochastic gradient algorithms are approximated in the weak sense by continuous-time stochastic differential equations. We exploit the continuous formulation together…

Machine Learning · Computer Science 2017-06-21 Qianxiao Li , Cheng Tai , Weinan E
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