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The higher-order nonlinear Schrodinger equation (Dysthe's equation in the context of water-waves) models the time evolution of the slowly modulated amplitude of a wave-packet in dispersive partial differential equations (PDE). These…

Analysis of PDEs · Mathematics 2024-12-18 Jack Keeler , Alberto Alberello , Ben Humphries , Emilian Parau

This book is an introduction to the theory of stochastic partial differential equations (SPDEs), using the random field approach pioneered by J.B. Walsh (1986). It consists of two blocks: the core matter (Chapters 1 to 6) and the appendices…

Probability · Mathematics 2026-02-17 Robert C. Dalang , Marta Sanz-Solé

A semiclassical theory of dissipative Henon-Heiles system is proposed. Based on $\hbar$-scaling of an equation for evolution of Wigner quasiprobability distribution function in presence of dissipation and thermal diffusion, we derive a…

chao-dyn · Physics 2015-06-24 Bidhan Chandra Bag , Deb Shankar Ray

We consider a class of one-dimensional nonlinear stochastic parabolic problems associated with Sellers and Budyko diffusive energy balance climate models with a Legendre weighted diffusion and an additive cylindrical Wiener processes…

Probability · Mathematics 2021-12-23 Gregorio Díaz , Jesús Ildefonso Díaz

This paper develops an asymptotic expansion technique in momentum space for stochastic filtering. It is shown that Fourier transformation combined with a polynomial-function approximation of the nonlinear terms gives a closed recursive…

Computational Finance · Quantitative Finance 2013-03-26 Masaaki Fujii

In this paper, we analyze the random fluctuations in a one dimensional stochastic homogenization problem and prove a central limit result, i.e., the first order fluctuations can be described by a Gaussian process that solves an SPDE with…

Probability · Mathematics 2015-08-24 Yu Gu

A type of discrete Boltzmann model for simulating shallow water flows is derived by using the Hermite expansion approach. Through analytical analysis, we study the impact of truncating distribution function and discretizing particle…

Fluid Dynamics · Physics 2018-07-16 Jianping Meng , Xiao-Jun Gu , David R Emerson , Yong Peng , Jianmin Zhang

This paper develops and analyzes some fully discrete mixed finite element methods for the stochastic Cahn-Hilliard equation with gradient-type multiplicative noise that is white in time and correlated in space. The stochastic Cahn-Hilliard…

Numerical Analysis · Mathematics 2019-03-14 Xiaobing Feng , Yukun Li , Yi Zhang

In statistical mechanics, evaluating finite-size macroscopic fluctuations typically relies on Edgeworth expansions. However, these perturbative methods append additive polynomial corrections that inevitably break down in the large deviation…

Information Theory · Computer Science 2026-04-15 Hiroki Suyari

We introduce a closed-form expansion for the transition density of elliptic and hypo-elliptic multivariate Stochastic Differential Equations (SDEs), over a period $\Delta\in (0,1)$, in terms of powers of $\Delta^{j/2}$, $j\ge 0$. Our…

Numerical Analysis · Mathematics 2025-09-17 Yuga Iguchi , Alexandros Beskos

This work focuses on the quantitative contraction rates for McKean-Vlasov stochastic differential equations (SDEs) with multiplicative noise. Under suitable conditions on the coefficients of the SDE, this paper derives explicit quantitative…

Probability · Mathematics 2025-09-30 Dan Noelck

We derive Edgeworth expansions that describe corrections to the Gaussian limiting behaviour of slow-fast systems. The Edgeworth expansion is achieved using a semi-group formalism for the transfer operator, where a Duhamel-Dyson series is…

Chaotic Dynamics · Physics 2019-02-05 Jeroen Wouters , Georg A. Gottwald

Accurately describing liquids and their mixtures beyond equilibrium remains a significant challenge in modern chemical physics and physical chemistry, especially regarding the calculation of transport properties in liquid-phase systems.…

Soft Condensed Matter · Physics 2025-06-19 Yury A. Budkov , Nikolai N. Kalikin , Petr E. Brandyshev

In this work, we study the numerical approximation of local fluctuations of certain classes of parabolic stochastic partial differential equations (SPDEs). Our focus is on effects for small spatially-correlated noise on a time scale before…

Numerical Analysis · Mathematics 2019-02-21 Christian Kuehn , Patrick Kuerschner

This paper develops high-order well-balanced (WB) energy stable (ES) finite difference schemes for multi-layer (the number of layers $M\geqslant 2$) shallow water equations (SWEs) on both fixed and adaptive moving meshes, extending our…

Numerical Analysis · Mathematics 2025-03-18 Zhihao Zhang , Huazhong Tang , Junming Duan

A new asymptotic expansion scheme for backward SDEs (BSDEs) is proposed.The perturbation parameter is introduced just to scale the forward stochastic variables within a BSDE. In contrast to the standard small-diffusion asymptotic expansion…

Computational Finance · Quantitative Finance 2014-12-23 Masaaki Fujii

High-order numerical methods for solving elliptic equations over arbitrary domains typically require specialized machinery, such as high-quality conforming grids for finite elements method, and quadrature rules for boundary integral…

Numerical Analysis · Mathematics 2021-06-02 Saad Qadeer , Boyce E. Griffith

These notes present an alternative approach to the asymptotic stability of stochastic partial differential equations driven by multiplicative noise, applicable to a wide range of dissipative systems. The method builds on general criteria…

Probability · Mathematics 2025-03-13 Ziyu Liu

We consider singular-degenerate, multivalued stochastic fast diffusion equations with multiplicative Lipschitz continuous noise. In particular, this includes the stochastic sign fast diffusion equation arising from the Bak-Tang-Wiesenfeld…

Probability · Mathematics 2015-01-08 Benjamin Gess , Michael Röckner

Stochastic differential equations (SDEs) are a ubiquitous modeling framework that finds applications in physics, biology, engineering, social science, and finance. Due to the availability of large-scale data sets, there is growing interest…

Machine Learning · Statistics 2025-03-04 Ziheng Guo , James Greene , Ming Zhong