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The forward-backward splitting method (FBS) for minimizing a nonsmooth composite function can be interpreted as a (variable-metric) gradient method over a continuously differentiable function which we call forward-backward envelope (FBE).…

Optimization and Control · Mathematics 2019-11-11 Lorenzo Stella , Andreas Themelis , Panagiotis Patrinos

In this paper we propose a numerical scheme for the class of backward doubly stochastic (BDSDEs) with possible path-dependent terminal values. We prove that our scheme converge in the strong $L^2$-sense and derive its rate of convergence.…

Probability · Mathematics 2011-08-04 Auguste Aman

We discuss the parallelization of algorithms for solving polynomial systems symbolically by way of triangular decomposition. Algorithms for solving polynomial systems combine low-level routines for performing arithmetic operations on…

Symbolic Computation · Computer Science 2019-06-04 Mohammadali Asadi , Alexander Brandt , Robert H. C. Moir , Marc Moreno Maza , Yuzhen Xie

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a…

Computational Physics · Physics 2017-12-06 Horacio V. Guzman , Christoph Junghans , Kurt Kremer , Torsten Stuehn

In this paper we obtain results for the existence and uniqueness of solutions to coupled Forward-Backward Stochastic Differential Equations (FBSDEs) with jumps defined on a random environment. This environment corresponds to a…

Probability · Mathematics 2024-01-19 Daniel Hernández-Hernández , Joshué Helí Ricalde-Guerrero

The discretization of elliptic PDEs leads to large coupled systems of equations. Domain decomposition methods (DDMs) are one approach to the solution of these systems, and can split the problem in a way that allows for parallel computing.…

Numerical Analysis · Mathematics 2019-08-01 Ian May , Ronald D. Haynes , Steven J. Ruuth

We propose a novel framework for solving a class of Partial Integro-Differential Equations (PIDEs) and Forward-Backward Stochastic Differential Equations with Jumps (FBSDEJs) through a deep learning-based approach. This method, termed the…

Numerical Analysis · Mathematics 2024-12-17 Zaijun Ye , Wansheng Wang

In this paper, a parallel overlapping domain decomposition preconditioner is proposed to solve the linear system of equations arising from the extended finite element discretization of elastic crack problems. The algorithm partitions the…

Computational Engineering, Finance, and Science · Computer Science 2021-12-07 Tian Wei , Huang Jingjing , Chen Rongliang , Jiang Yi

In this paper, we study the well-posedness of the Forward-Backward Stochastic Differential Equations (FBSDE) in a general non-Markovian framework. The main purpose is to find a unified scheme which combines all existing methodology in the…

Probability · Mathematics 2015-06-30 Jin Ma , Zhen Wu , Detao Zhang , Jianfeng Zhang

We propose a new algorithm to approach weakly the solution of a McKean-Vlasov SDE. Based on the cubature method of Lyons and Victoir 2004, the algorithm is deterministic differing from the the usual methods based on interacting particles.…

Probability · Mathematics 2019-04-22 Paul-Eric Chaudru de Raynal , Camilo Garcia Trillos

In this paper, we consider the fully coupled forward-backward stochastic functional differential equations (FBSFDEs) with stochastic functional differential equations as the forward equations and the generalized anticipated backward…

Probability · Mathematics 2013-12-05 Xiaoming Xu

This paper introduces a new approximation scheme for solving high-dimensional semilinear partial differential equations (PDEs) and backward stochastic differential equations (BSDEs). First, we decompose a target semilinear PDE (BSDE) into…

Numerical Analysis · Mathematics 2022-02-09 Akihiko Takahashi , Yoshifumi Tsuchida , Toshihiro Yamada

The athermal quasistatic deformation method provides an elegant solution to overcome the limitation of short time spans in molecular simulations. It provides overdamped conditions, allowing for the extraction of purely structural responses…

Computational Physics · Physics 2026-04-30 Maximilian Reihn , Franz Bamer , Benjamin Stamm

In [5] the authors obtained Mean-Field backward stochastic differential equations (BSDE) associated with a Mean-field stochastic differential equation (SDE) in a natural way as limit of some highly dimensional system of forward and backward…

Probability · Mathematics 2007-11-21 Rainer Buckdahn , Juan Li , Shige Peng

In this paper we present a novel sampling-based numerical scheme designed to solve a certain class of stochastic optimal control problems, utilizing forward and backward stochastic differential equations (FBSDEs). By means of a nonlinear…

Systems and Control · Computer Science 2020-06-18 Ioannis Exarchos , Evangelos A. Theodorou

We propose a parallel algorithm for the numerical solution of a class of second order semi-linear equations coming from stochastic optimal control problems, by means of a dynamic domain decomposition technique. The new method is an…

Numerical Analysis · Mathematics 2016-02-11 Simone Cacace , Maurizio Falcone

This paper investigates solvability of fully coupled systems of forward-backward stochastic differential equations (FBSDEs) with irregular coefficients. In particular, we assume that the coefficients of the FBSDEs are merely measurable and…

Probability · Mathematics 2020-04-02 Peng Luo , Olivier Menoukeu-Pamen , Ludovic Tangpi

A class of nonstandard pseudospectral time domain (PSTD) schemes for solving time-dependent hyperbolic and parabolic partial differential equations (PDEs) is introduced. These schemes use the Fourier collocation spectral method to compute…

Computational Physics · Physics 2018-03-23 Bradley E. Treeby , Elliott S. Wise , B. T. Cox

In this work we study a multi-step scheme on time-space grids proposed by W. Zhao et al. [28] for solving backward stochastic differential equations, where Lagrange interpolating polynomials are used to approximate the time-integrands with…

Numerical Analysis · Mathematics 2018-09-05 Long Teng , Aleksandr Lapitckii , Michael Günther

In this paper, we propose a deep learning based numerical scheme for strongly coupled FBSDEs, stemming from stochastic control. It is a modification of the deep BSDE method in which the initial value to the backward equation is not a free…

Optimization and Control · Mathematics 2023-02-10 Kristoffer Andersson , Adam Andersson , Cornelis W. Oosterlee