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A quantum kinetic theory of the spin transfer between carriers and Mn atoms in a Mn doped diluted magnetic semiconductor is presented. It turns out that the typical memory time associated with these processes is orders of magnitude shorter…

Mesoscale and Nanoscale Physics · Physics 2015-06-15 Christoph Thurn , Moritz Cygorek , Vollrath Martin Axt , Tilmann Kuhn

Even simply-defined, finite-state generators produce stochastic processes that require tracking an uncountable infinity of probabilistic features for optimal prediction. For processes generated by hidden Markov chains the consequences are…

Statistical Mechanics · Physics 2021-09-15 Alexandra M. Jurgens , James P. Crutchfield

In this paper, we introduce a class of processes that contains many natural examples. The interesting feature of such type processes lays on its infinite memory that allows it to record a quite ancient history. Then, using the martingale…

Probability · Mathematics 2025-03-04 Paul Doukhan , Xiequan Fan

Markovian memory embedded in a binary system is shaping its evolution on the basis of its current state and introduces either clustering or dispersion of binary states. The consequence is directly observed in the lengthening or shortening…

Applications · Statistics 2008-02-18 Fotini Pallikari , Nikitas Papasimakis

We consider the multilinear polynomial-form process \[X(n)=\sum_{1\le i_1<\ldots<i_k<\infty}a_{i_1}\ldots a_{i_k}\epsilon_{n-i_1}\ldots\epsilon_{n-i_k},\] obtained by applying a multilinear polynomial-form filter to i.i.d.\ sequence…

Probability · Mathematics 2013-04-19 Murad S. Taqqu , Shuyang Bai

Given a finite set $K$, we denote by $X=\Delta(K)$ the set of probabilities on $K$ and by $Z=\Delta_f(X)$ the set of Borel probabilities on $X$ with finite support. Studying a Markov Decision Process with partial information on $K$…

Optimization and Control · Mathematics 2012-02-29 Jérôme Renault , Xavier Venel

We present a comprehensive and up to date review on the concept of quantum non-Markovianity, a central theme in the theory of open quantum systems. We introduce the concept of quantum Markovian process as a generalization of the classical…

Quantum Physics · Physics 2014-08-26 Ángel Rivas , Susana F. Huelga , Martin B. Plenio

In this paper we consider the problem of binary hypothesis testing with finite memory systems. Let $X_1,X_2,\ldots$ be a sequence of independent identically distributed Bernoulli random variables, with expectation $p$ under $\mathcal{H}_0$…

Information Theory · Computer Science 2020-05-18 Tomer Berg , Ofer Shayevitz , Or Ordentlich

We consider two important time scales---the Markov and cryptic orders---that monitor how an observer synchronizes to a finitary stochastic process. We show how to compute these orders exactly and that they are most efficiently calculated…

Chaotic Dynamics · Physics 2014-04-23 Ryan G. James , John R. Mahoney , Christopher J. Ellison , James P. Crutchfield

Let W be the number of points in (0,t] of a stationary finite-state Markov renewal point process. We derive a bound for the total variation distance between the distribution of W and a compound Poisson distribution. For any nonnegative…

Probability · Mathematics 2007-05-23 Torkel Erhardsson

Suppose that $(X_t)_{t \ge 0}$ is a one-dimensional Brownian motion with negative drift $-\mu$. It is possible to make sense of conditioning this process to be in the state $0$ at an independent exponential random time and if we kill the…

Probability · Mathematics 2019-08-28 Steven N. Evans , Alexandru Hening

After reviewing the behavioral studies of working memory and of the cellular substrate of the latter, we argue that metastable states constitute candidates for the type of transient information storage required by working memory. We then…

Neurons and Cognition · Quantitative Biology 2024-03-18 Christophe Pouzat , Morgan André

A Markov Additive Process is a bi-variate Markov process $(\xi,J)=\big((\xi_t,J_t),t\geq0\big)$ which should be thought of as a multi-type L\'evy process: the second component $J$ is a Markov chain on a finite space $\{1,\ldots,K\}$, and…

Probability · Mathematics 2018-10-04 Robin Stephenson

Understanding the generative mechanism of a natural system is a vital component of the scientific method. Here, we investigate one of the fundamental steps toward this goal by presenting the minimal generator of an arbitrary binary Markov…

Statistical Mechanics · Physics 2018-02-14 J. Ruebeck , R. G. James , J. R. Mahoney , J. P. Crutchfield

We give a short overview of recent results on a specific class of Markov process: the Piecewise Deterministic Markov Processes (PDMPs). We first recall the definition of these processes and give some general results. On more specific cases…

Statistics Theory · Mathematics 2013-09-25 Romain Azaïs , Jean-Baptiste Bardet , Alexandre Genadot , Nathalie Krell , Pierre-André Zitt

We consider a pair of correlated processes {Z_n} and {S_n} (two sided), where the former is observable and the later is hidden. The uncertainty in the estimation of Z_n upon its finite past history is H(Z_n|Z_0^{n-1}), and for estimation of…

Information Theory · Computer Science 2007-07-13 Mohammad Rezaeian

We consider a risk-sensitive continuous-time Markov decision process over a finite time duration. Under the conditions that can be satisfied by unbounded transition and cost rates, we show the existence of an optimal policy, and the…

Optimization and Control · Mathematics 2018-11-29 Xin Guo , Qiuli Liu , Yi Zhang

For classical Markovian stochastic systems, past and future events become statistically independent when conditioned to a given state at the present time. Memory non-Markovian effects break this condition, inducing a non-vanishing…

Quantum Physics · Physics 2018-12-14 Adrián A. Budini

Recently, a series of different measures quantifying memory effects in the quantum dynamics of open systems has been proposed. Here, we derive a mathematical representation for the non-Markovianity measure based on the exchange of…

Let $X_1,X_2,\ldots$ and $Y_1,Y_2,\ldots$ be two random sequences so that every random variable takes values in a finite set $\mathbb{A}$. We consider a global similarity score $L_n:=L(X_1,\ldots,X_n;Y_1,\ldots,Y_n)$ that measures the…

Probability · Mathematics 2016-02-19 Jüri Lember , Heinrich Matzinger , Joonas Sova , Fabio Zucca