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Planar run-and-tumble walks with orthogonal directions of motion are considered. After formulating the problem with generic transition probabilities among the orientational states, we focus on the symmetric case, giving general expressions…

Statistical Mechanics · Physics 2022-12-26 Luca Angelani

We present here two new techniques to solve the one-dimensional random flight. The first one is an expansion in the number of collisions. The second one is the obtention of a Fourier series. This second technique can be applied to an…

Mathematical Physics · Physics 2023-06-30 Ricardo García-Pelayo

Real data are constrained to finite sampling rates, which calls for a suitable mathematical description of the corrections to the finite-time estimations of the dynamic equations. Often in the literature, lower order discrete time…

Data Analysis, Statistics and Probability · Physics 2015-05-13 C. Anteneodo , R. Riera

We consider a general class of stochastic optimal control problems, where the state process lives in a real separable Hilbert space and is driven by a cylindrical Brownian motion and a Poisson random measure; no special structure is imposed…

Probability · Mathematics 2018-10-04 Elena Bandini , Fulvia Confortola , Andrea Cosso

Lagrangian turbulence lies at the core of numerous applied and fundamental problems related to the physics of dispersion and mixing in engineering, bio-fluids, atmosphere, oceans, and astrophysics. Despite exceptional theoretical,…

The problem of diffusion in a time-dependent (and generally inhomogeneous) external field is considered on the basis of a generalized master equation with two times, introduced in [1,2]. We consider the case of the quasi Fokker-Planck…

Statistical Mechanics · Physics 2015-05-18 S. A. Trigger , G. J. F. van Heijst , O. F. Petrov , P. P. J. M. Schram

We introduce a new, probability-level approach to calculations in scalar field particle scattering. The approach involves the implicit summation over final states, which makes causality manifest since retarded propagators emerge naturally.…

High Energy Physics - Phenomenology · Physics 2025-09-17 Robert Dickinson , Jeff Forshaw , Ross Jenkinson , Peter Millington

We consider a tracer particle performing a random walk on a two-dimensional lattice in the presence of immobile hard obstacles. Starting from equilibrium, a constant force pulling on the particle is switched on, driving the system to a new…

Statistical Mechanics · Physics 2024-09-05 Dan Shafir , Alessio Squarcini , Stanislav Burov , Thomas Franosch

The general solution of the inverse Frobenius-Perron problem considering the construction of a fully chaotic dynamical system with given invariant density is obtained within the class of one-dimensional unimodal maps. Some interesting…

chao-dyn · Physics 2007-05-23 D. Pingel , P. Schmelcher , F. K. Diakonos

For a model convection-diffusion problem, we address the presence of oscillatory discrete solutions, and study difficulties in recovering standard approximation results for its solution. We justify the presence of non-physical oscillations…

Numerical Analysis · Mathematics 2026-01-15 Constantin Bacuta

This paper derives the Fokker-Planck (FP) equation for a particle moving in potential by a randomly modulated dipole. The FP equation describes the anomalous diffusion observed in the companion paper [1] and breaks the conservation of the…

Mathematical Physics · Physics 2022-05-03 S. Katagiri , Y. Matsuo , Y. Matsuoka , A. Sugamoto

In this paper, we provide a representation theory for the Feynman operator calculus. This allows us to solve the general initial-value problem and construct the Dyson series. We show that the series is asymptotic, thus proving Dyson's…

Mathematical Physics · Physics 2009-11-10 T. L. Gill , W. W Zachary

The random flights are (continuous time) random walkswith finite velocity. Often, these models describe the stochastic motions arising in biology. In this paper we study the large time asymptotic behavior of random flights. We prove the…

Probability · Mathematics 2012-11-30 Alessandro De Gregorio , Claudio Macci

Mathematical models based on probability density functions (PDF) have been extensively used in hydrology and subsurface flow problems, to describe the uncertainty in porous media properties (e.g., permeability modelled as random field).…

Fluid Dynamics · Physics 2020-06-01 Matteo Icardi , Marco Dentz

Higher orders in perturbation theory require the calculation of Feynman integrals at multiple loops. We report on an approach to systematically solve Feynman integrals by means of symbolic summation and discuss the underlying algorithms.…

Mathematical Physics · Physics 2008-11-26 S. Moch

Diffusion models have recently attained significant interest within the community owing to their strong performance as generative models. Furthermore, its application to inverse problems have demonstrated state-of-the-art performance.…

Image and Video Processing · Electrical Eng. & Systems 2022-03-22 Hyungjin Chung , Byeongsu Sim , Jong Chul Ye

We introduce an efficient configuration space technique which allows one to compute a class of Feynman diagrams which generalize the scalar sunset topology to any number of massive internal lines. General tensor vertex structures and…

High Energy Physics - Phenomenology · Physics 2009-10-31 S. Groote , J. G. Körner , A. A. Pivovarov

Consider directed polymers in a random environment on the complete graph of size $N$. This model can be formulated as a product of i.i.d. $N\times N$ random matrices and its large time asymptotics is captured by Lyapunov exponents and the…

Probability · Mathematics 2018-01-22 Francis Comets , Gregorio R. Moreno Flores , Alejandro F. Ramirez

A generalized Fokker-Planck equation is derived to describe particle kinetics in specific situations when the probability transition function (PTF) has a long tail in momentum space. The equation is valid for an arbitrary value of the…

Statistical Mechanics · Physics 2011-08-15 A. A. Dubinova , S. A. Trigger

Discrete diffusion models have recently emerged as a promising alternative to the autoregressive approach for generating discrete sequences. Sample generation via gradual denoising or demasking processes allows them to capture hierarchical…