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A stochastic leap-frog algorithm for the numerical integration of Brownian motion stochastic differential equations with multiplicative noise is proposed and tested. The algorithm has a second-order convergence of moments in a finite time…

Computational Physics · Physics 2009-10-31 Ji Qiang , Salman Habib

We present a novel application of the recently developed AAA algorithm to the solution of Laplace 2D problems; an application to conformal mapping is also shown as a particular case. These classes of problems have also been addressed by…

Numerical Analysis · Mathematics 2020-01-28 Stefano Costa

Self-consistent multi-particle simulation plays an important role in studying beam-beam effects and space charge effects in high-intensity beams. The Poisson equation has to be solved at each time-step based on the particle density…

Accelerator Physics · Physics 2014-10-15 J. Qiang , S. Paret

In a recent letter ({\it{EPL}}, {\bf{104}} (2013) 60003; see also {\it {arXiv:1309.5645}}), Plastino and Rocca suggest that the divergences inherent to the formulation of nonextensive statistical mechanics can be eliminated {\it {via}} the…

Statistical Mechanics · Physics 2014-02-04 James F. Lutsko , Jean Pierre Boon

In the (special) smoothing spline problem one considers a variational problem with a quadratic data fidelity penalty and Laplacian regularisation. Higher order regularity can be obtained via replacing the Laplacian regulariser with a…

Machine Learning · Statistics 2022-09-07 Nicolás García Trillos , Ryan Murray , Matthew Thorpe

State-space models are used to describe and analyse dynamical systems. They are ubiquitously used in many scientific fields such as signal processing, finance and ecology to name a few. Particle filters are popular inferential methods used…

Computation · Statistics 2024-12-20 Alaa Amri

This is a guide to the mathematical theory of Brownian motion and related stochastic processes, with indications of how this theory is related to other branches of mathematics, most notably the classical theory of partial differential…

Probability · Mathematics 2018-02-28 Jim Pitman , Marc Yor

This article deals with the numerical resolution of backward stochastic differential equations. Firstly, we consider a rather general case where the filtration is generated by a Brownian motion and a Poisson random measure. We provide a…

Probability · Mathematics 2008-12-18 Emmanuel Gobet , Jean-Philippe Lemor

Previously developed method for finding asymptotic solutions of Vlasov equations using two-dimensional (in coordinate x and time t) Laplace transform is applied to low-collision electron-ion plasmas. Taking into account Coulomb collisions…

Plasma Physics · Physics 2007-08-08 V. N. Soshnikov

Starting with a microscopic (individual-based) Brownian dynamics model of charged particles (ions), its macroscopic description is derived as a system of partial differential equations that govern the evolution of ion concentrations in…

Computational Physics · Physics 2025-06-25 Jinyuan Zhang , Radek Erban

In this note we propose a generalization of the Laplace and Fourier transforms which we call symmetric Laplace transform. It combines both the advantages of the Fourier and Laplace transforms. We give the definition of this generalization,…

Classical Analysis and ODEs · Mathematics 2017-01-31 Nikolaos Halidias

The problem of reconstruction of digital images from their degraded measurements is regarded as a problem of central importance in various fields of engineering and imaging sciences. In such cases, the degradation is typically caused by the…

Computer Vision and Pattern Recognition · Computer Science 2010-01-06 E. Shaked , O. Michailovich

We begin our journey by recalling the fundamentals of Probability Theory that underlie one of its most significant applications to real-world problems: Parametric Estimation. Throughout the text, we systematically develop this theme by…

Probability · Mathematics 2026-05-18 Levi Lopes de Lima

A formulation of the boundary integral method for solving partial differential equations has been developed whereby the usual weakly singular integral and the Cauchy principal value integral can be removed analytically. The broad…

Computational Physics · Physics 2019-10-02 E. Klaseboer , Q. Sun , D. Y. C. Chan

We introduce an evidence-driven Bayesian formulation of physics-informed neural networks that enables automatic optimization of loss weights between PDE residuals, boundary conditions, and observational data. Unlike existing Bayesian PINN…

Computational Physics · Physics 2026-05-29 Krzysztof M. Graczyk , Kornel Witkowski

Area openings and closings are morphological filters which efficiently suppress impulse noise from an image, by removing small connected components of level sets. The problem of an objective choice of threshold for the area remains open.…

Probability · Mathematics 2016-08-16 David Coupier , Agnès Desolneux , Bernard Ycart

Optical measurements often exhibit mixed Poisson-Gaussian noise statistics, which hampers image quality, particularly under low signal-to-noise ratio (SNR) conditions. Computational imaging falls short in such situations when solely…

Image and Video Processing · Electrical Eng. & Systems 2023-11-16 Jacob Seifert , Yifeng Shao , Rens van Dam , Dorian Bouchet , Tristan van Leeuwen , Allard P. Mosk

The problem of object restoration in the case of spatially incoherent illumination is considered. A regularized solution to the inverse problem is obtained through a probabilistic approach, and a numerical algorithm based on the statistical…

Optics · Physics 2009-11-13 Enrico De Micheli , Giovanni Alberto Viano

This survey provides an exposition of a suite of techniques based on the theory of polynomials, collectively referred to as polynomial methods, which have recently been applied to address several challenging problems in statistical…

Statistics Theory · Mathematics 2021-04-22 Yihong Wu , Pengkun Yang

Computer-aided engineering techniques are indispensable in modern engineering developments. In particular, partial differential equations are commonly used to simulate the dynamics of physical phenomena, but very large systems are often…

Quantum Physics · Physics 2022-04-26 Yuki Sato , Ruho Kondo , Satoshi Koide , Hideki Takamatsu , Nobuyuki Imoto