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We study the time evolution of quantum entanglement for a specific class of quantum dynamics, namely the locally scrambled quantum dynamics, where each step of the unitary evolution is drawn from a random ensemble that is invariant under…

Disordered Systems and Neural Networks · Physics 2020-07-01 Wei-Ting Kuo , A. A. Akhtar , Daniel P. Arovas , Yi-Zhuang You

We establish convergence to the Kingman coalescent for the genealogy of a geographically - or otherwise - structured version of the Wright-Fisher population model with fast migration. The new feature is that migration probabilities may…

Probability · Mathematics 2010-06-25 Serik Sagitov , Peter Jagers , Vladimir Vatutin

This paper gives a new flavor of what Peter Jagers and his co-authors call `the path to extinction'. In a neutral population with constant size $N$, we assume that each individual at time $0$ carries a distinct type, or allele. We consider…

Probability · Mathematics 2026-01-14 Guillaume Achaz , Amaury Lambert , Emmanuel Schertzer

We introduce a family of Markov processes on set partitions with a bounded number of blocks, called Lipschitz partition processes. We construct these processes explicitly by a Poisson point process on the space of Lipschitz continuous maps…

Statistics Theory · Mathematics 2015-06-05 Harry Crane

We study a class of Markovian systems of $N$ elements taking values in $[0,1]$ that evolve in discrete time $t$ via randomized replacement rules based on the ranks of the elements. These rank-driven processes are inspired by variants of the…

Probability · Mathematics 2012-01-06 Michael Grinfeld , Philip A. Knight , Andrew R. Wade

We consider exchangeable Markov multi-state survival processes -- temporal processes taking values over a state-space$\mathcal{S}$ with at least one absorbing failure state $\flat \in \mathcal{S}$ that satisfy natural invariance properties…

Methodology · Statistics 2018-10-26 Walter Dempsey

It is possible to represent each of a number of Markov chains as an evolving sequence of connected subsets of a directed acyclic graph that grow in the following way: initially, all vertices of the graph are unoccupied, particles are fed in…

Probability · Mathematics 2015-03-17 Steven N. Evans , Rudolf Gruebel , Anton Wakolbinger

In this paper, we consider the composition of two independent processes : one process corresponds to position and the other one to time. Such processes will be called iterated processes. We first propose an algorithm based on the Euler…

Probability · Mathematics 2017-05-03 Michèle Thieullen , Alexis Vigot

We consider a non-conserving zero-range process with hopping rate proportional to the number of particles at each site. Particles are added to the system with a site-dependent creation rate, and removed from the system with a uniform…

Statistical Mechanics · Physics 2019-09-04 Pascal Grange

We introduce an algorithm for generating a random sequence of fragmentation trees, which we call the ancestral branching algorithm. This algorithm builds on the recursive partitioning structure of a tree and gives rise to an associated…

Probability · Mathematics 2011-11-02 Harry Crane

The stochastic theory of non-relativistic quantum mechanics presented here relies heavily upon the theory of stochastic processes, with its definitions, theorems and specific vocabulary as well. Its main hypothesis states indeed that the…

Quantum Physics · Physics 2014-04-01 Maurice J. M. L. O. Godart

We describe the onset of condensation in the simple model for the balance between selection and mutation given by Kingman in terms of a scaling limit theorem. Loosely speaking, this shows that the wave moving towards genes of maximal…

Probability · Mathematics 2012-07-27 Steffen Dereich , Peter Mörters

Cross-Correlation random matrices have emerged as a promising indicator of phase transitions in spin systems. The core concept is that the evolution of magnetization encapsulates thermodynamic information [R. da Silva, Int. J. Mod. Phys. C,…

Statistical Mechanics · Physics 2024-08-19 Roberto da Silva , Sandra D. Prado

We develop a new Markov chain on graph partitions that makes relatively global moves yet is computationally feasible to be used as the proposal in the Metropolis-Hastings method. Our resulting algorithm can be made reversible and able to…

Data Structures and Algorithms · Computer Science 2021-05-11 Eric Autrey , Daniel Carter , Gregory Herschlag , Zach Hunter , Jonathan C. Mattingly

We present a flexible Bayesian semiparametric mixed model for longitudinal data analysis in the presence of potentially high-dimensional categorical covariates. Building on a novel hidden Markov tensor decomposition technique, our proposed…

Methodology · Statistics 2022-08-05 Giorgio Paulon , Peter Müller , Abhra Sarkar

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

We first study crossing statistics in random connection models (RCM) built on marked Poisson point processes on $\mathbb R^d$. Under general assumptions, we show exponential tail bounds for the number of crossings of a box contained in the…

Probability · Mathematics 2025-10-29 Alessandra Faggionato , Ivailo Hartarsky

The embedding problem of Markov transition matrices into continuous-time Markov semigroups is a classic problem that regained a lot of impetus and activities in recent years. We consider it here for the following generalisation of the…

Probability · Mathematics 2026-01-27 Ellen Baake , Michael Baake

We derive the general form of a master equation describing the interaction of an arbitrary multipartite quantum system, consisting of a set of subsystems, with an environment, consisting of a large number of sub-envirobments. Each subsystem…

Quantum Physics · Physics 2015-05-28 Vittorio Giovannetti , G. Massimo Palma

We consider Markov chains on the space of (countable) partitions of the interval $[0,1]$, obtained first by size biased sampling twice (allowing repetitions) and then merging the parts with probability $\beta_m$ (if the sampled parts are…

Probability · Mathematics 2007-05-23 Eddy Mayer-Wolf , Ofer Zeitouni , Martin P. W. Zerner