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We investigate the periodic and stationary solutions of distribution-dependent stochastic differential equations. While generally, the semigroups associated with the equations are nonlinear, we show that the methods of weak convergence and…

Probability · Mathematics 2025-01-17 Wei Sun , Ethan Wong

Tensor B-spline methods are a high-performance alternative to solve partial differential equations (PDEs). This paper gives an overview on the principles of Tensor B-spline methodology, shows their use and analyzes their performance in…

Numerical Analysis · Computer Science 2019-04-08 Dmytro Shulga , Oleksii Morozov , Volker Roth , Felix Friedrich , Patrick Hunziker

Classical convergence theory of Runge-Kutta methods assumes that the time step is small relative to the Lipschitz constant of the ordinary differential equation (ODE). For stiff problems, that assumption is often violated, and a problematic…

Numerical Analysis · Mathematics 2026-05-05 Steven B. Roberts , David Shirokoff , Abhijit Biswas , Benjamin Seibold

A new format for commutator-free Lie group methods is proposed based on explicit classical Runge-Kutta schemes. In this format exponentials are reused at every stage and the storage is required only for two quantities: the right hand side…

Numerical Analysis · Mathematics 2025-06-12 Alexei Bazavov

This paper investigate a class of multi-dimensional backward stochastic differential equations (BSDEs) with singualr generators exhibiting diagonally quadratic growth and unbounded terminal conditions, thereby extending results in the…

Probability · Mathematics 2025-07-08 Wenbo Wang , Guangyan Jia

In this article, we construct a representation formula for stochastic B-series evaluated in a B-series. This formula is used to give for the first time the order conditions of implicit Taylor methods in terms of rooted trees. Finally, as an…

Numerical Analysis · Mathematics 2011-01-26 Kristian Debrabant , Anne Kværnø

In this technical note a general procedure is described to construct internally consistent splitting methods for the numerical solution of differential equations, starting from matching pairs of explicit and diagonally implicit Runge-Kutta…

Numerical Analysis · Mathematics 2017-07-17 Willem Hundsdorfer

We establish existence and uniqueness for a wide class of Markovian systems of backward stochastic differential equations (BSDE) with quadratic nonlinearities. This class is characterized by an abstract structural assumption on the…

Probability · Mathematics 2017-03-10 Hao Xing , Gordan Žitković

In this paper, we investigate a class of nonlinear backward stochastic differential equations (BSDEs) arising from financial economics, and give specific information about the nodal sets of the related solutions. As applications, we are…

Probability · Mathematics 2022-11-01 Zengjing Chen , Shuhui Liu , Zhongmin Qian , Xingcheng Xu

In this work, we construct and derive a new class of exponentially fitted two-derivative diagonally implicit Runge--Kutta (EFTDDIRK) methods for the numerical solution of differential equations with oscillatory solutions. First, a general…

Numerical Analysis · Mathematics 2021-04-27 Julius O. Ehigie , Vu Thai Luan , Solomon A. Okunuga , Xiong You

We revisit the numerical stability of four well-established explicit stochastic integration schemes through a new generic benchmark stochastic differential equation designed to assess asymptotic statistical accuracy and stability…

Numerical Analysis · Mathematics 2026-05-20 Thomas Hudson , Sarah Helfert , Xingjie Helen Li

Retarded stochastic differential equations (SDEs) constitute a large collection of systems arising in various real-life applications. Most of the existing results make crucial use of dissipative conditions. Dealing with "pure delay" systems…

Probability · Mathematics 2013-08-12 Jianhai Bao , George Yin , Chenggui Yuan

Low-storage explicit Runge-Kutta schemes are particularly popular for the numerical integration of time-dependent partial differential equations based on the method-of-lines due to their efficiency and their reduced memory requirements. We…

Numerical Analysis · Mathematics 2026-04-07 Sergio Blanes , Alejandro Escorihuela-Tomàs

The distribution-dependent stochastic differential equations (DDSDEs) describe stochastic systems whose evolution is determined by both the microcosmic site and the macrocosmic distribution of the particle. The density function associated…

Probability · Mathematics 2017-04-18 Feng-Yu Wang

We apply exponential Runge Kutta time discretizations to semilinear evolution equations $\frac { {\rm d} U}{{\rm d} t}=AU+B(U)$ posed on a Hilbert space ${\mathcal Y}$. Here $A$ is normal and generates a strongly continuous semigroup, and…

Numerical Analysis · Mathematics 2019-11-15 Claudia Wulff

The goal of this project is to compare the performance of exponential time integrators with traditional methods such as diagonally implicit Runge-Kutta methods in the context of solving the system of reduced magnetohydrodynamics (RMHD). In…

Numerical Analysis · Mathematics 2022-07-07 Valentin Dallerit , Mayya Tokman , Ilon Joseph

In this paper, we present error estimates of fully discrete Runge--Kutta discontinuous Galerkin (DG) schemes for linear time-dependent partial differential equations. The analysis applies to explicit Runge--Kutta time discretizations of any…

Numerical Analysis · Mathematics 2020-01-07 Zheng Sun , Chi-Wang Shu

Backward Stochastic Differential Equations (BSDEs) have been widely employed in various areas of social and natural sciences, such as the pricing and hedging of financial derivatives, stochastic optimal control problems, optimal stopping…

Numerical Analysis · Mathematics 2023-04-10 Jared Chessari , Reiichiro Kawai , Yuji Shinozaki , Toshihiro Yamada

This paper (alongside its companion, Part II \cite{BSDEYoung-II}) investigates backward stochastic differential equations (BSDEs) involving a nonlinear Young integral of the form $\int_{t}^{T}g(Y_{r})\eta(dr,X_{r})$, where the driver…

Probability · Mathematics 2025-08-01 Jian Song , Huilin Zhang , Kuan Zhang

In this paper a new class of generalized backward doubly stochastic differential equations is investigated. This class involves an integral with respect to an adapted continuous increasing process. A probabilistic representation for…

Probability · Mathematics 2009-09-29 Brahim Boufoussi , Jan Van Casteren , N. Mrhardy
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