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Related papers: Yaglom limits can depend on the starting state

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We study a class of Piecewise Deterministic Markov Processes with state space Rd x E where E is a finite set. The continuous component evolves according to a smooth vector field that is switched at the jump times of the discrete coordinate.…

Probability · Mathematics 2014-04-08 Michel Benaïm , Stéphane Le Borgne , Florent Malrieu , Pierre-André Zitt

The methods of the probability theory have been used in order to build up a new model of hysteresis. It turns out that the reversal points of the control parameter (e. g., the magnetic field) are Markov points which determine the stochastic…

Statistical Mechanics · Physics 2009-10-31 L. Pal

Using elementary methods, we prove that for a countable Markov chain $P$ of ergodic degree $d > 0$ the rate of convergence towards the stationary distribution is subgeometric of order $n^{-d}$, provided the initial distribution satisfies…

Probability · Mathematics 2007-05-23 Stefano Isola

This paper proposes a new type of recurrence where we divide the Markov chains into intervals that start when the chain enters into a subset A, then sample another subset B far away from A and end when the chain again return to A. The…

Methodology · Statistics 2016-02-24 Lars Holden

We consider symmetric Markov chains on $\Bbb Z^d$ where we do {\bf not} assume that the conductance between two points must be zero if the points are far apart. Under a uniform second moment condition on the conductances, we obtain upper…

Probability · Mathematics 2007-05-23 Richard F. Bass , Takashi Kumagai

The eigenvalue absorption for a many-particle Hamiltonian depending on a parameter is analyzed in the framework of non--relativistic quantum mechanics. The long--range part of pair potentials is assumed to be pure Coulomb and no restriction…

Mathematical Physics · Physics 2008-07-21 D. K. Gridnev

We consider a family of measure preserving transformations, which act on a common probability space and are chosen at random by a stationary ergodic Markov chain. This setting defines an instance of a random dynamical system (RDS), which…

Dynamical Systems · Mathematics 2024-02-27 Pablo Lummerzheim , Felix Pogorzelski , Elias Zimmermann

For a discrete two-state quantum walk (QW) on the half-line with a general condition at the boundary, we formulate and prove a weak limit theorem describing the terminal behavior of its transition probabilities. In this context,…

Quantum Physics · Physics 2015-10-05 Chaobin Liu , Nelson Petulante

We consider a class of discrete time Markov chains with state space [0,1] and the following dynamics. At each time step, first the direction of the next transition is chosen at random with probability depending on the current location. Then…

Probability · Mathematics 2014-12-04 Shaun McKinlay , Konstantin Borovkov

We consider a random walk with catastrophes which was introduced to model population biology. It is known that this Markov chain gets eventually absorbed at $0$ for all parameter values. Recently, it has been shown that this chain exhibits…

Probability · Mathematics 2019-07-12 Luiz Renato Fontes , Rinaldo B. Schinazi

We consider a family of multivariate autoregressive stochastic sequences that restart when hit a neighbourhood of the origin, and study their distributional limits when the autoregressive coefficient tends to one, the noise scaling…

Probability · Mathematics 2020-11-20 Sergey Foss , Matthias Schulte

In this paper, we are concerned with centered Markov Additive Processes $\{(X_t,Y_t)\}_{t\in\T}$ where the driving Markov process $\{X_t\}_{t\in\T}$ has a finite state space. Under suitable conditions, we provide a local limit theorem for…

Probability · Mathematics 2013-06-25 Loïc Hervé , James Ledoux

Let $(X_n)_{n\geq 0}$ be a Markov chain with values in a finite state space $\mathbb X$ starting at $X_0=x \in \mathbb X$ and let $f$ be a real function defined on $\mathbb X$. Set $S_n=\sum_{k=1}^{n} f(X_k)$, $n\geqslant 1$. For any $y \in…

Probability · Mathematics 2017-07-20 Ion Grama , Ronan Lauvergnat , Emile Le Page

We give a closed form of the discrete-time evolution of a recombination transformation in population genetics. This decomposition allows to define a Markov chain in a natural way. We describe the geometric decay rate to the limit…

Probability · Mathematics 2016-03-24 Servet Martinez

We establish a functional weak law of large numbers for observable macroscopic state variables of interacting particle systems (e.g., voter and contact processes) over fast time-varying sparse random networks of interactions. We show that,…

Probability · Mathematics 2017-03-01 Augusto Almeida Santos , Soummya Kar , José M. F. Moura , João Xavier

Let $(X_t, Y_t)_{t\in T}$ be a discrete or continuous-time Markov process with state space $X \times R^d$ where $X$ is an arbitrary measurable set. Its transition semigroup is assumed to be additive with respect to the second component,…

Probability · Mathematics 2012-07-27 Deborah Ferre , Loïc Hervé , James Ledoux

Many years ago B.S. Pitskel observed that the metric entropy of the shift transformation in the sample space of a stationary random process $X=\{X_n,\,n\in \mathbb Z\}$ with a countable number of states is equal to the conditional entropy…

Dynamical Systems · Mathematics 2016-06-03 Boris Gurevich

We present a generic threshold model for the co-evolution of the structure of a network and the state of its nodes. We focus on regular directed networks and derive equations for the evolution of the system toward its absorbing state. It is…

Physics and Society · Physics 2009-06-19 Renaud Lambiotte , Juan Carlos Gonzalez-Avella

Discontinuous transition is observed in the equilibrium cluster properties of a percolation model with suppressed cluster growth as the growth parameter g0 is tuned to the critical threshold at sufficiently low initial seed concentration…

Statistical Mechanics · Physics 2016-07-28 B. Roy , S. B. Santra

We prove deviation bounds for the random variable $\sum_{i=1}^{n} f_i(Y_i)$ in which $\{Y_i\}_{i=1}^{\infty}$ is a Markov chain with stationary distribution and state space $[N]$, and $f_i: [N] \rightarrow [-a_i, a_i]$. Our bound improves…

Probability · Mathematics 2019-04-02 Shravas Rao
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