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Random walks with stochastic resetting provides a treatable framework to study interesting features about central-place motion. In this work, we introduce non-instantaneous resetting as a two-state model being a combination of an exploring…

Statistical Mechanics · Physics 2019-10-23 Axel Masó-Puigdellosas , Daniel Campos , Vicenç Méndez

Fractional Brownian motion and the fractional Langevin equation are models of anomalous diffusion processes characterized by long-range power-law correlations in time. We employ large-scale computer simulations to study these models in two…

Statistical Mechanics · Physics 2021-04-22 Thomas Vojta , Alex Warhover

Functionals of particles' paths have diverse applications in physics, mathematics, hydrology, economics, and other fields. Under the framework of continuous time random walk (CTRW), the governing equations for the probability density…

Statistical Mechanics · Physics 2018-11-21 Xudong Wang , Yao Chen , Weihua Deng

We consider a model of random tree growth, where at each time unit a new vertex is added and attached to an already existing vertex chosen at random. The probability with which a vertex with degree $k$ is chosen is proportional to $w(k)$,…

Probability · Mathematics 2007-05-23 Anna Rudas , Balint Toth , Benedek Valko

The concept of continuous-time random walks (CTRW) is a generalization of ordinary random walk models, and it is a powerful tool for investigating a broad spectrum of phenomena in natural, engineering, social and economic sciences.…

Statistical Mechanics · Physics 2015-06-12 Hamid Teimouri , Anatoly B. Kolomeisky

Probabilistic graphical models are a powerful concept for modeling high-dimensional distributions. Besides modeling distributions, probabilistic graphical models also provide an elegant framework for performing statistical inference;…

Artificial Intelligence · Computer Science 2022-09-13 Christian Knoll

Branching processes are widely used to model the viral epidemic evolution. For more adequate investigation of viral epidemic modelling, we suggest to apply branching processes with transport of particles usually called branching random…

Probability · Mathematics 2019-01-29 Elizaveta Ermakova , Polina Makhmutova , Elena Yarovaya

Turbulence is essential for understanding the structure and dynamics of molecular clouds and star-forming regions. There is a need for adequate tools to describe and characterize the properties of turbulent flows. One-point probability…

Astrophysics · Physics 2008-11-26 Ralf S. Klessen

We consider the problem of estimating the joint distribution of a continuous-time perpetuity and the underlying factors which govern the cash flow rate, in an ergodic Markov model. Two approaches are used to obtain the distribution. The…

Probability · Mathematics 2016-01-18 Constantinos Kardaras , Scott Robertson

The gravitational evolution of the cosmic one-point Probability Distribution Function (PDF) can be estimated using an analytic approximation that combines gravitational Perturbation Theory (PT) with the Edgeworth expansion around a Gaussian…

Astrophysics · Physics 2007-05-23 P. Fosalba , E. Gaztanaga , E. Elizalde

Reinforced random walks (RRWs), including vertex-reinforced random walks (VRRWs) and edge-reinforced random walks (ERRWs), model random walks where the transition probabilities evolve based on prior visitation history~\cite{mgr, fmk,…

Machine Learning · Statistics 2026-05-22 Qinghua , Ding , Venkat Anantharam

Random walks constitute a fundamental mechanism for a large set of dynamics taking place on networks. In this article, we study random walks on weighted networks with an arbitrary degree distribution, where the weight of an edge between two…

Statistical Mechanics · Physics 2013-01-17 Zhongzhi Zhang , Tong Shan , Guanrong Chen

In the context of order statistics of discrete time random walks (RW), we investigate the statistics of the gap, $G_n$, and the number of time steps, $L_n$, between the two highest positions of a Markovian one-dimensional random walker,…

Statistical Mechanics · Physics 2014-09-17 Satya N. Majumdar , Philippe Mounaix , Gregory Schehr

Reinforced random walks are random walks on graphs whose transition probabilities along edges from a vertex are proportional to the weights of those edges, but where the weight of an edge evolves in a way that depends on the past traversals…

Information Theory · Computer Science 2026-05-22 Qinghua , Ding , Venkat Anantharam

Low-dimensional periodic arrays of scatterers with a moving point particle are ideal models for studying deterministic diffusion. For such systems the diffusion coefficient is typically an irregular function under variation of a control…

Chaotic Dynamics · Physics 2009-11-07 R. Klages , N. Korabel

Let $\tau = (\tau_i : i \in {\Bbb Z})$ denote i.i.d.~positive random variables with common distribution $F$ and (conditional on $\tau$) let $X = (X_t : t\geq0, X_0=0)$, be a continuous-time simple symmetric random walk on ${\Bbb Z}$ with…

Probability · Mathematics 2007-05-23 L. R. G. Fontes , M. Isopi , C. M. Newman

Random walk models, such as the trap model, continuous time random walks, and comb models exhibit weak ergodicity breaking, when the average waiting time is infinite. The open question is: what statistical mechanical theory replaces the…

Statistical Mechanics · Physics 2007-05-23 Golan Bel , Eli Barkai

We revisit the one dimensional discrete time quantum walk with 3 states and the Grover coin. We derive analytic expressions for observed the localization, an long time approximation for the probability density function (PDF). We also…

Quantum Physics · Physics 2014-10-29 Stefan Falkner , Stefan Boettcher

In a continuous time random walk (CTRW), each random jump follows a random waiting time. CTRW scaling limits are time-changed processes that model anomalous diffusion. The outer process describes particle jumps, and the non-Markovian inner…

Probability · Mathematics 2016-11-29 Mark M. Meerschaert , Erkan Nane , Yimin Xiao

In natural phenomena, data distributions often deviate from normality. One can think of cataclysms as a self-explanatory example: events that occur almost never, and at the same time are many standard deviations away from the common…

Machine Learning · Computer Science 2022-12-16 Nuno Costa , Nuno Moniz
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