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Related papers: The structure of combinatorial Markov processes

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Bohm-Bell processes, of interest in the foundations of quantum field theory, form a class of Markov processes $Q_t$ generalizing in a natural way both Bohm's dynamical system in configuration space for nonrelativistic quantum mechanics and…

Quantum Physics · Physics 2007-05-23 Roderich Tumulka

Any single system whose space of states is given by a separable Hilbert space is automatically equipped with infinitely many hidden tensor-like structures. This includes all quantum mechanical systems as well as classical field theories and…

Quantum Physics · Physics 2024-02-16 Marek Czachor

We consider a class of stochastic dynamical systems, called piecewise deterministic Markov processes, with states $(x, \s)\in \O\times \G$, $\O$ being a region in $\bbR^d$ or the $d$--dimensional torus, $\G$ being a finite set. The…

Statistical Mechanics · Physics 2009-02-25 Alessandra Faggionato , Davide Gabrielli , Marco Ribezzi Crivellari

We study two different types of vector point processes with interacting components, introducing a migration-type effect. The first case concerns two groups which modify their states with rate functions depending on time only. This yields a…

Probability · Mathematics 2025-10-15 Fabrizio Cinque , Enzo Orsingher

A function on the state space of a Markov chain is a "lumping" if observing only the function values gives a Markov chain. We give very general conditions for lumpings of a large class of algebraically-defined Markov chains, which include…

Combinatorics · Mathematics 2018-06-19 C. Y. Amy Pang

We suggest a new mean field method for studying the thermodynamic competition between magnetic and superconducting phases in a two-dimensional square lattice. A partition function is constructed by writing microscopic interactions that…

Superconductivity · Physics 2009-11-13 Benoit Vanderheyden , A D Jackson

Given a level set $E$ of an arbitrary multiplicative function $f$, we establish, by building on the fundamental work of Frantzikinakis and Host [13,14], a structure theorem which gives a decomposition of $\mathbb{1}_E$ into an almost…

Number Theory · Mathematics 2022-05-16 Vitaly Bergelson , Joanna Kułaga-Przymus , Mariusz Lemańczyk , Florian K. Richter

Scientific explanation often requires inferring maximally predictive features from a given data set. Unfortunately, the collection of minimal maximally predictive features for most stochastic processes is uncountably infinite. In such…

Statistical Mechanics · Physics 2017-05-31 Sarah E. Marzen , James P. Crutchfield

We investigate a piecewise-deterministic Markov process, evolving on a Polish metric space, whose deterministic behaviour between random jumps is governed by some semi-flow, and any state right after the jump is attained by a randomly…

Probability · Mathematics 2020-12-04 Dawid Czapla , Sander C. Hille , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

This document presents a combinatorial framework for analyzing assembly systems using generating functions. We explore the theory through concrete examples, such as linear polymers, and develop recursive equations to characterize valid…

Combinatorics · Mathematics 2025-01-22 Andrés Ortiz-Muñoz

Consider a non-explosive positive Feller process with no negative jumps. It is shown in this note that when infinity is an entrance boundary, in the sense that the entrance times of the process remain bounded when the initial value tends to…

Probability · Mathematics 2020-06-16 Clément Foucart , Pei-Sen Li , Xiaowen Zhou

In this paper, we consider a subclass of piecewise deterministic Markov processes with a Polish state space that involve a deterministic motion punctuated by random jumps, occurring in a Poisson-like fashion with some state-dependent rate,…

Probability · Mathematics 2024-05-28 Dawid Czapla

The hitting and mixing times are two fundamental quantities associated with Markov chains. In Peres and Sousi[PS2015] and Oliveira[Oli2012], the authors show that the mixing times and "worst-case" hitting times of reversible Markov chains…

Probability · Mathematics 2019-04-05 Robert M. Anderson , Haosui Duanmu , Aaron Smith

We consider a fractional counting process with jumps of amplitude $1,2,\ldots,k$, with $k\in \mathbb{N}$, whose probabilities satisfy a suitable system of fractional difference-differential equations. We obtain the moment generating…

Probability · Mathematics 2016-03-10 Antonio Di Crescenzo , Barbara Martinucci , Alessandra Meoli

An analogue of the classical Mecke formula for Poisson point processes is proved for the class of space-time STIT tessellation processes. From this key identity the Markov property of a class of associated random processes is derived. This…

Probability · Mathematics 2017-11-06 Werner Nagel , Linh Ngoc Nguyen , Christoph Thaele , Viola Weiss

We seek to infer the parameters of an ergodic Markov process from samples taken independently from the steady state. Our focus is on non-equilibrium processes, where the steady state is not described by the Boltzmann measure, but is…

Statistical Mechanics · Physics 2018-02-19 Simon Lee Dettmer , Johannes Berg

Many seemingly disparate Markov chains are unified when viewed as random walks on the set of chambers of a hyperplane arrangement. These include the Tsetlin library of theoretical computer science and various shuffling schemes. If only…

Combinatorics · Mathematics 2010-02-08 Christos A. Athanasiadis , Persi Diaconis

The Poisson process of order $i$ is a weighted sum of independent Poisson processes and is used to model the flow of clients in different services. In the paper below we study some extensions of this process, for different forms of the…

Probability · Mathematics 2019-10-01 A. Maheshwari , E. Orsingher , A. S. Sengar

In this note we show that the locally stationary wavelet process can be decomposed into a sum of signals, each of which following a moving average process with time-varying parameters. We then show that such moving average processes are…

Methodology · Statistics 2009-01-27 K. Triantafyllopoulos , G. P. Nason

Recently Belopolskaya and Suhov studied Markov process's in a random environment, where the environment changes in likeness to a Markov process. Constructions were made to allow the process to "interact with the environment", this was done…

Probability · Mathematics 2017-04-07 Anirban Das