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We establish the existence and uniqueness of strong solutions, in both the PDE and probabilistic sense, for a broad class of nonlinear stochastic partial differential equations (SPDEs) on a bounded domain $\mathscr{O}\subset \mathbb{R}^d$…

Analysis of PDEs · Mathematics 2025-12-16 Agus L. Soenjaya , Thanh Tran

We develop the in-out formalism for one-loop effective actions in electromagnetic fields in the space-dependent gauge. We further advance a method using the inverse scattering matrix to calculate the effective actions in pure magnetic…

High Energy Physics - Theory · Physics 2011-07-22 Sang Pyo Kim

We calculate the one-loop effective potential at finite temperature for a system of massless scalar fields with quartic interaction $\lambda\phi^4$ in the framework of the boundary effective theory (BET) formalism. The calculation relies on…

High Energy Physics - Phenomenology · Physics 2011-06-30 A. Bessa , C. A. A. de Carvalho , E. S. Fraga , F. Gelis

Recently, in a paper by Jentzen and Kloeden [Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci. 465 (2009) 649-667], a new method for simulating nearly linear stochastic partial differential equations (SPDEs) with additive noise has been…

Probability · Mathematics 2012-11-01 Arnulf Jentzen , Peter Kloeden , Georg Winkel

The sample-function regularity of the random-field solution to a stochastic partial differential equation (SPDE) depends naturally on the roughness of the external noise, as well as on the properties of the underlying integro-differential…

Probability · Mathematics 2023-11-21 Davar Khoshnevisan , Marta Sanz-Solé

In this paper a new approach for constructing \emph{multivariate} Gaussian random fields (GRFs) using systems of stochastic partial differential equations (SPDEs) has been introduced and applied to simulated data and real data. By solving a…

Methodology · Statistics 2013-07-08 Xiangping Hu , Daniel Simpson , Finn Lindgren , Håvard Rue

We study strictly parabolic stochastic partial differential equations on $\R^d$, $d\ge 1$, driven by a Gaussian noise white in time and coloured in space. Assuming that the coefficients of the differential operator are random, we give…

Probability · Mathematics 2007-05-23 Marco Ferrante , Marta Sanz-Solé

Using a path integral formulation for correlation functions of stochastic partial differential equations based on the Onsager-Machlup approach, we show how, by introducing a composite auxiliary field one can generate an auxiliary field loop…

Statistical Mechanics · Physics 2014-06-12 Fred Cooper

In this paper, we consider the numerical approximation of a general second order semilinear stochastic partial differential equation (SPDE) driven by multiplicative and additive noise. Our main interest is on such SPDEs where the nonlinear…

Numerical Analysis · Mathematics 2020-11-19 Jean Daniel Mukam , Antoine Tambue

We present a systematic treatment of non-Gaussianity in stochastic systems using the Schwinger-Keldysh effective field theory framework, in which the non-Gaussianity is realized as nonlinear terms in the fluctuation field. We establish two…

High Energy Physics - Theory · Physics 2024-02-15 Shu Lin , Yanyan Bu , Chang Lei

Supergeometric Quantum Field Theories (SG-QFTs) are theories that go beyond the standard supersymmetric framework, since they allow for general scalar-fermion field transformations on the configuration space of a supermanifold, without…

High Energy Physics - Theory · Physics 2024-10-04 Viola Gattus , Apostolos Pilaftsis

This paper aims to investigate the numerical approximation of semilinear non-autonomous stochastic partial differential equations (SPDEs) driven by multiplicative or additive noise. Such equations are more realistic than autonomous SPDEs…

Numerical Analysis · Mathematics 2020-11-18 Jean Daniel Mukam , Antoine Tambue

Understanding the properties of the stochastic phase field models is crucial to model processes in several practical applications, such as soft matters and phase separation in random environments. To describe such random evolution, this…

Numerical Analysis · Mathematics 2023-03-13 Jianbo Cui , Dianming Hou , Zhonghua Qiao

In a previous paper, we studied the ergodic properties of an Euler scheme of a stochastic differential equation with a Gaussian additive noise in order to approximate the stationary regime of such equation. We now consider the case of…

Probability · Mathematics 2013-11-20 Serge Cohen , Fabien Panloup , Samy Tindel

Gaussian fields (GFs) are frequently used in spatial statistics for their versatility. The associated computational cost can be a bottleneck, especially in realistic applications. It has been shown that computational efficiency can be…

Computation · Statistics 2015-03-13 Xiaoyu Liu , Serge Guillas , Ming-Jun Lai

This article offers sharp spatial and temporal mean-square regularity results for a class of semi-linear parabolic stochastic partial differential equations (SPDEs) driven by infinite dimensional fractional Brownian motion with the Hurst…

Numerical Analysis · Mathematics 2020-08-04 Xiaojie Wang , Ruisheng Qi , Fengze Jiang

We study a class of elliptic SPDEs with additive Gaussian noise on $\mathbb{R}^2 \times M$, with $M$ a $d$-dimensional manifold equipped with a positive Radon measure, and a real-valued non linearity given by the derivative of a smooth…

Probability · Mathematics 2020-08-04 Sergio Albeverio , Francesco C. De Vecchi , Massimiliano Gubinelli

We investigate the one-loop effective action for a test scalar field in a general Friedmann-Lema\^itre-Robertson-Walker (FLRW) background, specifically focusing on quantum corrections up to the second order in the interaction strength. By…

General Relativity and Quantum Cosmology · Physics 2026-02-02 Will Cerne , Teruaki Suyama

Stochastic differential equations (SDEs) and stochastic partial differential equations (SPDEs) are fundamental for modeling stochastic dynamics across the natural sciences and modern machine learning. Learning their solution operators with…

Machine Learning · Computer Science 2026-01-30 Dai Shi , Lequan Lin , Andi Han , Luke Thompson , José Miguel Hernández-Lobato , Zhiyong Wang , Junbin Gao

We present a method, based on the Keldysh formalism, for deriving stochastic master equations that describe the non-Markovian dynamics of a quantum system coupled to a Gaussian environment. This approach yields a compact expression for the…

Quantum Physics · Physics 2026-01-21 Vasco Cavina , Antonio D'Abbruzzo , Vittorio Giovannetti