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The asymptotic behavior of a subcritical Branching Process in Random Environment (BPRE) starting with several particles depends on whether the BPRE is strongly subcritical (SS), intermediate subcritical (IS) or weakly subcritical (WS).…

Probability · Mathematics 2008-12-10 Vincent Bansaye

In this paper the asymptotic behavior of a critical multi-type branching process with immigration is described when the offspring mean matrix is irreducible, in other words, when the process is indecomposable. It is proved that sequences of…

Probability · Mathematics 2014-01-16 Tivadar Danka , Gyula Pap

We consider an indecomposable Galton-Watson branching process with countably infinitely many types. Assuming that the process is critical and allowing for infinite variance of the offspring sizes of some (or all) types of particles we…

Probability · Mathematics 2020-03-02 V. A. Topchii , V. A. Vatutin , E. E. Dyakonova

A stochastic partial differential equation (SPDE) is derived for super-Brownian motion regarded as a distribution function valued process. The strong uniqueness for the solution to this SPDE is obtained by an extended Yamada-Watanabe…

Probability · Mathematics 2013-03-21 Jie Xiong

This paper introduces time-continuous numerical schemes to simulate stochastic differential equations (SDEs) arising in mathematical finance, population dynamics, chemical kinetics, epidemiology, biophysics, and polymeric fluids. These…

Probability · Mathematics 2015-03-13 Nawaf Bou-Rabee , Eric Vanden-Eijnden

Special functions have always played a central role in physics and in mathematics, arising as solutions of nonlinear differential equations, as well as in the theory of branching processes, which extensively uses probability generating…

Probability · Mathematics 2026-05-14 Penka Mayster , Assen Tchorbadjieff

The nonequilibrium steady state (NESS) of integrable spin chains experiencing strong boundary dissipation is accounted by introducing quasiparticles with a renormalized -- dissipatively dressed -- dispersion relation. This allows us to…

Statistical Mechanics · Physics 2025-05-23 Vladislav Popkov , Xin Zhang , Carlo Presilla , Tomaž Prosen

Models defined by stochastic differential equations (SDEs) allow for the representation of random variability in dynamical systems. The relevance of this class of models is growing in many applied research areas and is already a standard…

Methodology · Statistics 2014-08-06 Umberto Picchini

In this paper we present a martingale related to the exit measures of super-Brownian motion. By changing measure with this martingale in the canonical way we have a new process associated with the conditioned exit measure. This measure is…

Probability · Mathematics 2016-11-01 Thomas S. Salisbury , John Verzani

Scaling limits for continuous-time branching processes with discrete state space are provided as the initial state tends to infinity. Depending on the finiteness or non-finiteness of the mean and/or the variance of the offspring…

Probability · Mathematics 2021-05-05 Martin Möhle , Benedict Vetter

We study a genealogical model for continuous-state branching processes with immigration with a (sub)critical branching mechanism. This model allows the immigrants to be on the same line of descent. The corresponding family tree is an…

Probability · Mathematics 2008-02-13 Thomas Duquesne

Consider a branching process $\{Z_n\}_{n\ge 0}$ with immigration in varying environment. For $a\in\{0,1,2,...\},$ let $C=\{n\ge0:Z_n=a\}$ be the collection of times at which the population size of the process attains level $a.$ We give a…

Probability · Mathematics 2023-08-08 Hua-Ming Wang

We extend earlier results on conditioning of super-Brownian motion to general branching rules. We obtain representations of the conditioned process, both as an $h$-transform, and as an unconditioned superprocess with immigration along a…

Probability · Mathematics 2011-03-10 Siva R. Athreya , Thomas S. Salisbury

We develop a new continuous-time stochastic gradient descent method for optimizing over the stationary distribution of stochastic differential equation (SDE) models. The algorithm continuously updates the SDE model's parameters using an…

Machine Learning · Computer Science 2023-08-29 Ziheng Wang , Justin Sirignano

A general class of non-Markov, supercritical Gaussian branching particle systems is introduced and its long-time asymptotics is studied. Both weak and strong laws of large numbers are developed with the limit object being characterized in…

Probability · Mathematics 2018-07-30 Michael A. Kouritzin , Khoa Lê , Deniz Sezer

Fragmentation processes are part of a broad class of models describing the evolution of a system of particles which split apart at random. These models are widely used in biology, materials science and nuclear physics, and their asymptotic…

Probability · Mathematics 2020-07-23 Quan Shi , Alexander R. Watson

Fast development in science and technology has driven the need for proper statistical tools to capture special data features such as abrupt changes or sharp contrast. Many inverse problems in data science require spatiotemporal solutions…

Methodology · Statistics 2025-10-21 Shiwei Lan , Mirjeta Pasha , Shuyi Li , Weining Shen

The nonlinear branching process with immigration is constructed as the pathwise unique solution of a stochastic integral equation driven by Poisson ran- dom measures. Some criteria for the regularity, recurrence, ergodicity and strong…

Probability · Mathematics 2017-01-20 Pei-Sen Li

Spontaneous symmetry breaking (SSB) and exceptional points (EPs) are often assumed to be inherently linked. Here we investigate the intricate relationship between SSB and specific classes of EPs across three distinct, real-world scenarios…

The distributions of $ N $-particle systems of Gaussian unitary ensembles converge to Sine$_2$ point processes under bulk-scaling limits. These scalings are parameterized by a macro-position $ \theta $ in the support of the semicircle…

Probability · Mathematics 2018-03-29 Yosuke Kawamoto , Hirofumi Osada
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