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The birth-death process is a special type of continuous-time Markov chain with index set $\mathbb{N}$. Its resolvent matrix can be fully characterized by a set of parameters $(\gamma, \beta, \nu)$, where $\gamma$ and $\beta$ are…

Probability · Mathematics 2024-09-10 Liping Li

We introduce and study a fractional variant of the linear birth-death process, namely, the generalized fractional linear birth-death process (GFLBDP) which is defined by taking the regularized Hilfer-Prabhakar derivative in the system of…

Probability · Mathematics 2025-02-12 Manisha Dhillon , Pradeep Vishwakarma , Kuldeep Kumar Kataria

Gibbs measures, such as Coulomb gases, are popular in modelling systems of interacting particles. Recently, we proposed to use Gibbs measures as randomized numerical integration algorithms with respect to a target measure $\pi$ on $\mathbb…

Machine Learning · Computer Science 2025-08-05 Rémi Bardenet , Mylène Maïda , Martin Rouault

This article studies the quasi-stationary behaviour of population processes with unbounded absorption rate, including one-dimensional birth and death processes with catastrophes and multi-dimensional birth and death processes, modeling…

Probability · Mathematics 2016-11-10 Nicolas Champagnat , Denis Villemonais

Bayesian inference plays a central role in scientific and engineering applications by enabling principled reasoning under uncertainty. However, sampling from generic probability distributions remains a computationally demanding task. This…

Applications · Statistics 2025-09-03 Alex Leviyev , Francesco Iacovelli , Aaron Zimmerman

There has been recently a lot of interest in the analysis of the Stein gradient descent method, a deterministic sampling algorithm. It is based on a particle system moving along the gradient flow of the Kullback-Leibler divergence towards…

Analysis of PDEs · Mathematics 2023-12-29 José A. Carrillo , Jakub Skrzeczkowski

We consider Markov processes that alternate continuous motions and jumps in a general locally compact polish space. Starting from a mechanistic construction, a first contribution of this article is to provide conditions on the dynamics so…

Probability · Mathematics 2022-04-07 Ronan Le Guével , Frédéric Lavancier , Emilien Manent

We consider a one dimensional transport model with nonlocal velocity given by the Hilbert transform and develop a global well-posedness theory of probability measure solutions. Both the viscous and non-viscous cases are analyzed. Both in…

Analysis of PDEs · Mathematics 2011-11-01 J. A. Carrillo , L. C. F. Ferreira , J. C. Precioso

A Kawasaki dynamics in continuum is a dynamics of an infinite system of interacting particles in $\mathbb R^d$ which randomly hop over the space. In this paper, we deal with an equilibrium Kawasaki dynamics which has a Gibbs measure $\mu$…

Probability · Mathematics 2007-08-20 Y. G. Kondratiev , O. V. Kutoviy , E. W. Lytvynov

We consider an extended birth-death-immigration process defined on a lattice formed by the integers of $d$ semiaxes joined at the origin. When the process reaches the origin, then it may jumps toward any semiaxis with the same rate. The…

Probability · Mathematics 2016-06-07 Antonio Di Crescenzo , Barbara Martinucci , Abdelaziz Rhandi

We investigate free-energy dissipation in a continuous-time birth-and-death dynamics in $\mathbb{R}^d$. For these Markov processes, the class of reversible measures coincides with the infinite-volume Gibbs point processes for some…

Probability · Mathematics 2026-02-17 Benedikt Jahnel , Jonas Köppl , Yannic Steenbeck , Alexander Zass

We prove that for every locally stable and tempered pair potential $\phi$ with bounded range, there exists a unique infinite-volume Gibbs point process on $\mathbb{R}^d$ for every activity $\lambda < (e^{L} \hat{C}_{\phi})^{-1}$, where $L$…

Probability · Mathematics 2024-07-02 Samuel Baguley , Andreas Göbel , Marcus Pappik

Diffusion models for continuous state spaces based on Gaussian noising processes are now relatively well understood from both practical and theoretical perspectives. In contrast, results for diffusion models on discrete state spaces remain…

Machine Learning · Computer Science 2026-04-02 Giovanni Conforti , Alain Durmus , Le-Tuyet-Nhi Pham , Gael Raoul

In order to model random density-dependence in population dynamics, we construct the random analogue of the well-known logistic process in the branching process' framework. This density-dependence corresponds to intraspecific competition…

Probability · Mathematics 2007-05-23 Amaury Lambert

We propose and analyze a class of adaptive sampling algorithms for multimodal distributions on a bounded domain, which share a structural resemblance to the classic overdamped Langevin dynamics. We first demonstrate that this class of…

Machine Learning · Computer Science 2024-11-26 Björn Engquist , Kui Ren , Yunan Yang

The Gibbs sampler (a.k.a. Glauber dynamics and heat-bath algorithm) is a popular Markov Chain Monte Carlo algorithm which iteratively samples from the conditional distributions of a probability measure $\pi$ of interest. Under the…

Probability · Mathematics 2026-01-21 Filippo Ascolani , Hugo Lavenant , Giacomo Zanella

We propose a new deterministic growth model which captures certain features of both the Gompertz and Korf laws. We investigate its main properties, with special attention to the correction factor, the relative growth rate, the inflection…

Populations and Evolution · Quantitative Biology 2016-10-31 Antonio Di Crescenzo , Serena Spina

In a first part, we prove a Lyapunov-type criterion for the $\xi\_1$-positive recurrence of absorbed birth and death processes and provide new results on the domain of attraction of the minimal quasi-stationary distribution. In a second…

Probability · Mathematics 2015-01-29 Denis Villemonais

When a system is swept through a quantum critical point, the quantum Kibble-Zurek mechanism makes universal predictions for quantities such as the number and energy of excitations produced. This mechanism is now being used to obtain…

Quantum Physics · Physics 2023-02-09 Nicholas E. Sherman , Alexander Avdoshkin , Joel E. Moore

We develop a continuous mathematical model of population dynamics that describes the sequential emergence of new genotypes under limited resources. The framework models genotype density as a nonlinear flow in mutation space, combining…

Populations and Evolution · Quantitative Biology 2025-12-10 Alexander Bratus , Tatiana Yakushkina , Vladimir Posvyanski