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We consider triangular arrays of Markov chains that converge weakly to a diffusion process. Second order Edgeworth type expansions for transition densities are proved. The paper differs from recent results in two respects. We allow…

Statistics Theory · Mathematics 2007-05-23 Valentin Konakov , Enno Mammen

We establish the convergence of the densities of a sequence of nonlinear functionals of an underlying Gaussian process to the density of a Gamma distribution. The key idea of our work is a new density formula for random variables in the…

Probability · Mathematics 2025-11-17 Solesne Bourguin , Thanh Dang , Yaozhong Hu

Let $X_n(k)$ be the number of vertices at level $k$ in a random recursive tree with $n+1$ vertices. We are interested in the asymptotic behavior of $X_n(k)$ for intermediate levels $k=k_n$ satisfying $k_n\to\infty$ and $k_n=o(\log n)$ as…

Probability · Mathematics 2018-06-29 Alexander Iksanov , Zakhar Kabluchko

We prove convergence of symmetric diffusions on Wiener spaces by using stopping times arguments and capacity techniques. The drifts of the diffusions can be singular, we require the densities of the processes to be neither bounded from…

Probability · Mathematics 2007-05-23 Andrea Posilicano , Tusheng Zhang

In evolutionary dynamics, a key measure of a mutant trait's success is the probability that it takes over the population given some initial mutant-appearance distribution. This "fixation probability" is difficult to compute in general, as…

Populations and Evolution · Quantitative Biology 2022-02-18 Alex McAvoy , Benjamin Allen

We characterize a class of Markovian dynamics using the concept of divisible dynamical map. Moreover we provide a family of criteria which can distinguish Markovian and non-Markovian dynamics. These Markovianity criteria are based on a…

Quantum Physics · Physics 2012-09-03 Dariusz Chruściński , Andrzej Kossakowski

Interacting particle systems undergoing repeated mutation and selection steps model genetic evolution, and also describe a broad class of sequential Monte Carlo methods. The genealogical tree embedded into the system is important in both…

Probability · Mathematics 2023-04-20 Suzie Brown , Paul A. Jenkins , Adam M. Johansen , Jere Koskela

Is studied asymptotic expansion for solution of singularly perturbed equation for functional of Markovian evolution in Rd. The view of regular and singular parts of solution is found.

Probability · Mathematics 2009-10-21 I. V. Samoilenko

We consider the motion of a particle governed by a weakly random Hamiltonian flow. We identify temporal and spatial scales on which the particle trajectory converges to a spatial Brownian motion. The main technical issue in the proof is to…

Mathematical Physics · Physics 2009-11-11 T. Komorowski , L. Ryzhik

The weak-strong uniqueness for Maxwell--Stefan systems and some generalized systems is proved. The corresponding parabolic cross-diffusion equations are considered in a bounded domain with no-flux boundary conditions. The key points of the…

Analysis of PDEs · Mathematics 2021-10-12 Xiaokai Huo , Ansgar Jüngel , Athanasios E. Tzavaras

We study the large population limit of the Moran process, assuming weak-selection, and for different scalings. Depending on the particular choice of scalings, we obtain a continuous model that may highlight the genetic-drift (neutral…

Populations and Evolution · Quantitative Biology 2013-01-21 Fabio A. C. C. Chalub , Max O. Souza

This paper studies the asymptotic behavior of processes with switching. More precisely, the stability under fast switching for diffusion processes and discrete state space Markovian processes is considered. The proofs are based on…

Probability · Mathematics 2017-07-07 Sören Christensen , Albrecht Irle

The goal of this paper is to define an evolution equation for a curve of random probability measures $(M_t)_{t\in[0,T]}\subset \mathcal{P}(\mathcal{P}(\mathbb{R}^d))$ associated to a non-local drift $b:[0,T]\times\mathbb{R}^d \times…

Analysis of PDEs · Mathematics 2025-10-10 Alessandro Pinzi

Obvious view of distribution function of Markovian random evolution is found in terms of Bessel functions of n+1-th order.

Probability · Mathematics 2009-11-03 I. V. Samoilenko

The evolution of a complex multi-state system is often interpreted as a continuous-time Markovian process. To model the relaxation dynamics of such systems, we introduce an ensemble of random sparse matrices which can be used as generators…

Statistical Mechanics · Physics 2023-07-19 Goran Nakerst , Sergey Denisov , Masudul Haque

A fairly general procedure is studied to perturbate a multivariate density satisfying a weak form of multivariate symmetry, and to generate a whole set of non-symmetric densities. The approach is general enough to encompass a number of…

Methodology · Statistics 2009-11-13 Adelchi Azzalini , Antonella Capitanio

The paper deals with a certain class of random evolutions. We develop a construction that yields an invariant measure for a continuous-time Markov process with random transitions. The approach is based on a particular way of constructing…

Probability · Mathematics 2015-10-20 Y. Belopolskaya , Y. Suhov

We perform a systematic symmetry classification of the Markov generators of classical stochastic processes. Our classification scheme is based on the action of involutive symmetry transformations of a real Markov generator, extending the…

Statistical Mechanics · Physics 2025-03-13 Lucas Sá , Pedro Ribeiro , Tomaž Prosen , Denis Bernard

The nonlinear evolution of an ion ring instability in a low-beta magnetospheric plasma is considered. The evolution of the two-dimensional ring distribution is essentially quasilinear. Ignoring nonlinear processes the time-scale for the…

Plasma Physics · Physics 2015-05-27 M. Mithaiwala , L. Rudakov1 , G. Ganguli , C. Crabtree

We prove the existence of weak solutions of It\^o's stochastic time dependent equations with irregular diffusion and drift terms of Morrey spaces. Weak uniqueness (generally conditional) and a conjecture pertaining to strong solutions are…

Probability · Mathematics 2024-09-16 N. V. Krylov