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Related papers: Solving mean field rough differential equations

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In this paper, we propose an efficient and flexible algorithm to solve dynamic mean-field planning problems based on an accelerated proximal gradient method. Besides an easy-to-implement gradient descent step in this algorithm, a crucial…

Optimization and Control · Mathematics 2021-03-01 Jiajia Yu , Rongjie Lai , Wuchen Li , Stanley Osher

We develop a relativistic mean field (RMF) description of deformed nuclei with the pairing correlations in the BCS approximation. The treatment of the pairing correlations for nuclei with the Fermi surface being close to the threshold of…

Nuclear Theory · Physics 2009-11-10 L. S. Geng , H. Toki , S. Sugimoto , J. Meng

This paper establishes the averaging method to a coupled system consisting of two stochastic differential equations which has a slow component driven by fractional Brownian motion (FBM) with less regularity $1/3< H \leq 1/2$ and a fast…

Probability · Mathematics 2023-07-26 Bin Pei , Robert Hesse , Bjoern Schmalfuss , Yong Xu

We construct the "expected signature matching" estimator for differential equations driven by rough paths and we prove its consistency and asymptotic normality. We use it to estimate parameters of a diffusion and a fractional diffusions,…

Probability · Mathematics 2011-12-16 Anastasia Papavasiliou , Christophe Ladroue

The statement of the mean field approximation theorem in the mean field theory of Markov processes particularly targets the behaviour of population processes with an unbounded number of agents. However, in most real-world engineering…

Probability · Mathematics 2017-05-11 Mahmoud Talebi , Jan Friso Groote , Jean-Paul Linnartz

In this paper, we prove a large deviation principle of Freidlin-Wentzell's type for the multivalued stochastic differential equations. As an application, we derive a functional iterated logarithm law for the solutions of multivalued…

Probability · Mathematics 2015-05-12 Jiagang Ren , Jing Wu , Hua Zhang

The method of this paper is my original creation. A new method for solving linear differential equations is proposed in this paper. The important conclusion of this paper is that arbitrary order linear ordinary differential equations with…

General Mathematics · Mathematics 2018-06-05 Daiyuan Zhang

In this work we show that rough stochastic differential equations (RSDEs), as introduced by Friz, Hocquet, and L\^e (2021), are Malliavin differentiable. We use this to prove existence of a density when the diffusion coefficients satisfies…

Probability · Mathematics 2024-02-20 Fabio Bugini , Michele Coghi , Torstein Nilssen

The purpose of this paper is to provide a complete probabilistic analysis of a large class of stochastic differential games for which the interaction between the players is of mean-field type. We implement the Mean-Field Games strategy…

Probability · Mathematics 2012-10-23 Rene Carmona , Francois Delarue

The Lane-Emden type equations are employed in the modelling of several phenomena in the areas of mathematical physics and astrophysics . In this paper a new numerical method is applied to investigate some well-known classes of Lane-Emden…

Numerical Analysis · Mathematics 2016-05-27 Kourosh Parand , Soleiman Hashemi

We study a class of semi-implicit Taylor-type numerical methods that are easy to implement and designed to solve multidimensional stochastic differential equations driven by a general rough noise, e.g. a fractional Brownian motion. In the…

Numerical Analysis · Mathematics 2020-06-25 Sebastian Riedel , Yue Wu

We present a numerical solution of the dynamical mean field theory of infinite-dimensional equilibrium liquids established in [Phys. Rev. Lett. 116, 015902 (2016)]. For soft sphere interactions, we obtain the numerical solution by an…

Statistical Mechanics · Physics 2020-04-28 Alessandro Manacorda , Grégory Schehr , Francesco Zamponi

In this article, we consider elliptic diffusion problems on random domains with non-smooth diffusion coefficients. We start by illustrating the problems that arise from a non-smooth diffusion coefficient by recapitulating the corresponding…

Numerical Analysis · Mathematics 2019-05-15 M. D. Multerer

In this paper, we study reflected differential equations driven by continuous paths with finite $p$-variation ($1\le p<2$) and $p$-rough paths ($2\le p<3$) on domains in Euclidean spaces whose boundaries may not be smooth. We define…

Probability · Mathematics 2015-04-24 Shigeki Aida

Motivated by the recent advances in the theory of stochastic partial differential equations involving nonlinear functions of distributions, like the Kardar-Parisi-Zhang (KPZ) equation, we reconsider the unique solvability of one-dimensional…

Probability · Mathematics 2015-03-09 François Delarue , Roland Diel

We study solutions to backward differential equations that are driven hybridly by a deterministic discontinuous rough path $W$ of finite $q$-variation for $q \in [1, 2)$ and by Brownian motion $B$. To distinguish between integration of…

Probability · Mathematics 2025-05-28 Dirk Becherer , Yuchen Sun

We consider solutions to an elliptic partial differential equation in $\mathbb{R}^d$ with a stationary, random conductivity coefficient. The boundary condition on a square domain of width $L$ is chosen so that the solution has a macroscopic…

Probability · Mathematics 2014-06-10 James Nolen

We propose a new method for constructing exact solutions to nonlinear delay reaction--diffusion equations of the form $$ u_t=ku_{xx}+F(u,w), $$ where $u=u(x,t)$, $w=u(x,t-\tau)$, and $\tau$ is the delay time. The method is based on…

Exactly Solvable and Integrable Systems · Physics 2013-04-22 Andrei D. Polyanin , Alexei I. Zhurov

We introduce a notion of rough paths on embedded submanifolds and demonstrate that this class of rough paths is natural. On the way we develop a notion of rough integration and an efficient and intrinsic theory of rough differential…

Probability · Mathematics 2017-05-17 Thomas Cass , Bruce K. Driver , Christian Litterer

We present a condition for a stochastic differential equation dX_{t}={\mu}(t,X_{t})dt+{\sigma}(t,X_{t})dB_{t} to have a unique functional solution of the form Z(t,B_{t}). The condition expresses a relation between {\mu} and {\sigma}. A…

Probability · Mathematics 2012-09-05 Imme van den Berg