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Stochastic differential equations, especially the one called Langevin equation, play an important role in many fields of modern science. In this paper, we use the bicolour rooted tree method, which is based on the stochastic Taylor…

Computational Physics · Physics 2015-06-11 Jiabin You , Hong Zhao

We extend the Ito -to- Stratonovich analysis or quantum stochastic differential equations, introduced by Gardiner and Collett for emission (creation), absorption (annihilation) processes, to include scattering (conservation) processes.…

Mathematical Physics · Physics 2009-11-11 John Gough

Since the seminal work of Wiener, the chaos expansion has evolved to a powerful methodology for studying a broad range of stochastic differential equations. Yet its complexity for systems subject to the white noise remains significant. The…

Numerical Analysis · Mathematics 2018-06-28 M. H. Gorji

We present numerical schemes for the strong solution of linear stochastic differential equations driven by an arbitrary number of Wiener processes. These schemes are based on the Neumann (stochastic Taylor) and Magnus expansions. Firstly,…

Numerical Analysis · Mathematics 2007-08-22 Gabriel Lord , Simon J. A. Malham , Anke Wiese

The coefficients of the stochastic differential equations with Markovian switching (SDEwMS) additionally depend on a Markov chain and there is no notion of differentiating such functions with respect to the Markov chain. In particular, this…

Probability · Mathematics 2022-11-22 Tejinder Kumar , Chaman Kumar

A procedure is described for defining a generalized solution for stochastic differential equations using the Cameron-Martin version of the Wiener Chaos expansion. Existence and uniqueness of this Wiener Chaos solution is established for…

Probability · Mathematics 2007-06-19 S. V. Lototsky , B. L. Rozovskii

This article is devoted to the stochastic anticipating equations with the extended stochastic integral with respect to the Gaussian processes of a special type. In the particular cases the solutions of such an equations are the well-known…

Probability · Mathematics 2007-05-23 Andrey A Dorogovtsev

The article is devoted to the construction of explicit one-step numerical methods with the strong orders of convergence 2.0, 2,5, and 3.0 for Ito stochastic differential equations with multidimensional non-commutative noise. We consider the…

Probability · Mathematics 2022-08-18 Dmitriy F. Kuznetsov

The article is devoted to the construction of explicit one-step strong numerical methods with the orders 2.0 and 2.5 of convergence for Ito stochastic differential equations with multidimensional non-commutative noise. We consider the…

Probability · Mathematics 2022-09-13 Dmitriy F. Kuznetsov

The study of multidimensional stochastic processes involves complex computations in intricate functional spaces. In particular, the diffusion processes, which include the practically important Gauss-Markov processes, are ordinarily defined…

Probability · Mathematics 2010-09-06 Thibaud Taillefumier , Jonathan Touboul

A general way of representing Stochastic Differential Equations (SDEs) on smooth manifold is based on Schwartz morphism. In this manuscript we are interested in SDEs on a smooth manifold $M$ that are driven by p-dimensional Wiener process…

Differential Geometry · Mathematics 2023-07-28 Sumit Suthar , Soumyendu Raha

Functional It\^o calculus was introduced in order to expand a functional $F(t, X\_{\cdot+t}, X\_t)$ depending on time $t$, past and present values of the process $X$. Another possibility to expand $F(t, X\_{\cdot+t}, X\_t)$ consists in…

Probability · Mathematics 2015-05-15 Andrea Cosso , Francesco Russo

We consider linearizations of stochastic differential equations with additive noise using the Karhunen-Lo\`eve expansion. We obtain our linearizations by truncating the expansion and writing the solution as a series of matrix-vector…

Numerical Analysis · Mathematics 2020-04-14 Antti Koskela , Samuel D. Relton

The article is devoted to a new proof of the expansion for iterated Ito stochastic integrals with respect to the components of a multidimensional Wiener process. The above expansion is based on Hermite polynomials and generalized multiple…

Probability · Mathematics 2024-01-01 Dmitriy F. Kuznetsov

The article is devoted to the expansion of iterated Stratonovich stochastic integrals of multiplicity 2 on the base of the combined approach of generalized multiple and iterated Fourier series. We consider two different parts of the…

Probability · Mathematics 2026-02-13 Dmitriy F. Kuznetsov

The aim of this paper is to present an elementary computable theory of probability, random variables and stochastic processes. The probability theory is baed on existing approaches using valuations and lower integrals. Various approaches to…

Probability · Mathematics 2015-10-14 Pieter Collins

We use the displacement operator to derive an infinite series of integer order derivatives for the Gr\"{u}nwald-Letnikov fractional derivative and show its correspondence to the Riemann-Liouville and Caputo fractional derivatives. We…

Numerical Analysis · Mathematics 2018-01-12 Anastasia Gladkina , Gavriil Shchedrin , U. Al Khawaja , Lincoln D. Carr

Taylor expansions of analytic functions are considered with respect to several points, allowing confluence of any of them. Cauchy-type formulas are given for coefficients and remainders in the expansions, and the regions of convergence are…

Classical Analysis and ODEs · Mathematics 2007-05-23 José L. López , Nico M. Temme

Many important index transforms can be constructed via the spectral theory of Sturm-Liouville differential operators. Using the spectral expansion method, we investigate the general connection between the index transforms and the associated…

Classical Analysis and ODEs · Mathematics 2018-06-18 Rúben Sousa , Semyon Yakubovich

The article is devoted to the implementation of strong numerical methods with convergence orders $0.5,$ $1.0,$ $1.5,$ $2.0,$ $2.5,$ and $3.0$ for Ito stochastic differential equations with multidimensional non-commutative noise based on the…

Probability · Mathematics 2025-05-23 Mikhail D. Kuznetsov , Dmitriy F. Kuznetsov