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We study a (relativistic) Wiener process on a complexified (pseudo-)Riemannian manifold. Using Nelson's stochastic quantization procedure, we derive three equivalent descriptions for this problem. If the process has a purely real quadratic…

Mathematical Physics · Physics 2022-05-17 Folkert Kuipers

We revisit the work of Mitter and Newton on an information-theoretic interpretation of Bayes' formula through the Gibbs variational principle. This formulation allowed them to pose nonlinear estimation for diffusion processes as a problem…

Optimization and Control · Mathematics 2024-05-02 Maxim Raginsky

This paper analyzes the discretization of a Neumann boundary control problem with a stochastic parabolic equation, where an additive noise occurs in the Neumann boundary condition. The convergence is established for general filtrations, and…

Optimization and Control · Mathematics 2022-09-07 Qin Zhou , Binjie Li

Stochastic Taylor expansions of the expectation of functionals applied to diffusion processes which are solutions of stochastic differential equation systems are introduced. Taylor formulas w.r.t. increments of the time are presented for…

Probability · Mathematics 2013-10-24 Andreas Rößler

We consider a class of linear Vlasov partial differential equations driven by Wiener noise. Different types of stochastic perturbations are treated: additive noise, multiplicative It\^o and Stratonovich noise, and transport noise. We…

Numerical Analysis · Mathematics 2024-03-01 Charles-Edouard Bréhier , David Cohen

We consider a Markov process on a Riemannian manifold, which solves a stochastic differential equation in the interior of the manifold and jumps according to a deterministic reset map when it reaches the boundary. We derive a partial…

Probability · Mathematics 2007-05-23 Julien Bect , Hana Baili , Gilles Fleury

We study the Cauchy problem for Schr\"odinger type stochastic partial differential equations with uniformly bounded coefficients on a curved space. We give conditions on the coefficients, on the drift and diffusion terms, on the Cauchy…

Analysis of PDEs · Mathematics 2022-08-29 Alessia Ascanelli , Sandro Coriasco , André Süß

We consider the task of generating discrete-time realisations of a nonlinear multivariate diffusion process satisfying an It\^o stochastic differential equation conditional on an observation taken at a fixed future time-point. Such…

Computation · Statistics 2016-04-26 Gavin A. Whitaker , Andrew Golightly , Richard J. Boys , Chris Sherlock

The solution of a (stochastic) differential equation (SDE) can be locally approximated by a stochastic expansion, a linear combination of iterated integrals. Quantities of interest, like moments, can then be approximated with the expansion.…

Probability · Mathematics 2010-08-25 Christophe Ladroue

We study a class of stochastic semilinear damped wave equations driven by additive Wiener noise. Owing to the damping term, under appropriate conditions on the nonlinearity, the solution admits a unique invariant distribution. We apply…

Numerical Analysis · Mathematics 2023-06-27 Ziyi Lei , Charles-Edouard Bréhier , Siqing Gan

In this paper, we consider stochastic Schroedinger equations with two-dimensional white noise. Such equations are used to describe the evolution of an open quantum system undergoing a process of continuous measurement. Representations are…

Mathematical Physics · Physics 2011-08-17 J. Gough , O. O. Obrezkov , O. G. Smolyanov

We study the stochastic solution to a Cauchy problem for a degenerate parabolic equation arising from option pricing. When the diffusion coefficient of the underlying price process is locally H\"older continuous with exponent $\delta\in (0,…

Probability · Mathematics 2021-07-15 Xiaoshan Chen , Yu-Jui Huang , Qingshuo Song , Chao Zhu

In this paper Gaussian models of retarded and accelerated anomalous diffusion are considered. Stochastic differential equations of fractional order driven by single or multiple fractional Gaussian noise terms are introduced to describe…

Statistical Mechanics · Physics 2014-05-08 Chai Hok Eab , S. C. Lim

The traditional wave equation models wave propagation in an ideal conducting medium. For characterizing the wave propagation in inhomogeneous media with frequency dependent power-law attenuation, the space-time fractional wave equation…

Numerical Analysis · Mathematics 2017-12-22 Yajing Li , Yejuan Wang , Weihua Deng

We study unique solvability for one dimensional stochastic pressure equation with diffusion coefficient given by the Wick exponential of log-correlated Gaussian fields. We prove well-posedness for Dirichlet, Neumann and periodic boundary…

Probability · Mathematics 2025-12-02 Benny Avelin , Tuomo Kuusi , Patrik Nummi , Eero Saksman , Jonas M. Tölle , Lauri Viitasaari

With the use of Hida's white noise space theory space theory and spaces of stochastic distributions, we present a detailed analytic continuation theory for classes of Gaussian processes, with focus here on Brownian motion. For the latter,…

Probability · Mathematics 2025-01-27 Luis Daniel Abreu , Daniel Alpay , Tryphon Georgiou , Palle Jorgensen

We consider a stochastic extension of the nonlocal convective Cahn-Hilliard equation containing an additive Wiener process noise. We first introduce a suitable analytical setting and make some mathematical and physical assumptions. We then…

Probability · Mathematics 2016-03-08 Federico Cornalba

This article proposes a new filtering model for stationary Gaussian Markov statistical experiments, given by diffusion-type difference stochastic equations.

Statistics Theory · Mathematics 2020-07-01 V. S. Koroliuk , D. Koroliouk

We consider an open model possessing a Markovian quantum stochastic limit and derive the limit stochastic Schrodinger equations for the wave function conditioned on indirect observations using only the von Neumann projection postulate. We…

Quantum Physics · Physics 2007-05-23 John Gough , Andrei Sobolev

We propose a fast algorithm for the probabilistic solution of boundary value problems (BVPs), which are ordinary differential equations subject to boundary conditions. In contrast to previous work, we introduce a Gauss--Markov prior and…

Machine Learning · Statistics 2021-06-16 Nicholas Krämer , Philipp Hennig