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We study the asymptotic behavior of the number of paths of length $N$ on several classes of infinite graphs with a single special vertex. This vertex can work as an entropic trap for the path, i.e. under certain conditions the dominant part…

Statistical Mechanics · Physics 2017-05-24 S. K. Nechaev , M. V. Tamm , O. V. Valba

We consider two random walks evolving synchronously on a random out-regular graph of $n$ vertices with bounded out-degree $r\ge 2$, also known as a random Deterministic Finite Automaton (DFA). We show that, with high probability with…

Probability · Mathematics 2023-11-30 Matteo Quattropani , Federico Sau

In this paper we study localized states in a monitored evolution on a finite graph and how they are distinguished from the delocalized states in terms of the transition probabilities and the mean transition times. Monitoring is performed by…

Quantum Physics · Physics 2025-02-17 Klaus Ziegler

It is known that maximal entropy random walks and partition functions that count long paths on graphs tend to become localized near nodes with a high degree. Here, we revisit the simplest toy model of such a localization: a regular tree of…

Statistical Mechanics · Physics 2023-09-22 Alexey V. Gulyaev , Mikhail V. Tamm

The one-dimensional random trap model with a power-law distribution of mean sojourn times exhibits a phenomenon of dynamical localization in the case where diffusion is anomalous: The probability to find two independent walkers at the same…

Data Analysis, Statistics and Probability · Physics 2015-03-03 Franziska Flegel , Igor M. Sokolov

Thermodynamic conventions suffer from describing dynamical distinctions, especially when the structural and energetic changes induced by localized rare events are insignificant. By using the ensemble theory in the trajectory space, we…

Statistical Mechanics · Physics 2023-03-30 Qi-Jun Ye , Xin-Zheng Li

Phase transitions are a fundamental concept in science describing diverse phenomena ranging from, e.g., the freezing of water to Bose-Einstein condensation. While the concept is well-established in equilibrium, similarly fundamental…

We discuss walking behavior in gauge theories and weak first-order phase transitions in statistical physics. Despite appearing in very different systems (QCD below the conformal window, the Potts model, deconfined criticality) these two…

High Energy Physics - Theory · Physics 2018-11-14 Victor Gorbenko , Slava Rychkov , Bernardo Zan

Dynamical phase transitions (DPTs) in the space of trajectories are one of the most intriguing phenomena of nonequilibrium physics, but their nature in realistic high-dimensional systems remains puzzling. Here we observe for the first time…

Statistical Mechanics · Physics 2017-09-07 N. Tizón-Escamilla , C. Pérez-Espigares , P. L. Garrido , P. I. Hurtado

In this paper, we present an overview of different types of random walk strategies with local and non-local transitions on undirected connected networks. We present a general approach to analyzing these strategies by defining the dynamics…

Statistical Mechanics · Physics 2020-07-08 A. P. Riascos , José L. Mateos

We study a family of diffusively coupled chaotic maps on periodic d-dimensional square lattices. Even and odd sub-lattices are updated alternately, introducing an effective delay. As the coupling strength is increased, the system undergoes…

Statistical Mechanics · Physics 2010-09-16 P. K. Mohanty

We introduce a self-organized model of graph evolution associated with preferential network random walkers. The idea is developed by using two different types of walkers, the interactions of which lead to a dynamic graph. The walkers of the…

Statistical Mechanics · Physics 2012-06-01 S. Mehraban , M. R. Ejtehadi

It has been well established that spatially extended, bistable systems that are driven by an oscillating field exhibit a nonequilibrium dynamic phase transition (DPT). The DPT occurs when the field frequency is on the order of the inverse…

Statistical Mechanics · Physics 2007-05-23 G. Korniss , P. A. Rikvold , M. A. Novotny

We introduce a modified model of random walk, and then develop two novel clustering algorithms based on it. In the algorithms, each data point in a dataset is considered as a particle which can move at random in space according to the…

Machine Learning · Computer Science 2008-10-31 Qiang Li , Yan He , Jing-ping Jiang

We consider a random walk on a $d$-regular graph $G$ where $d\to\infty$ and $G$ satisfies certain conditions. Our prime example is the $d$-dimensional hypercube, which has $n=2^d$ vertices. We explore the likely component structure of the…

Combinatorics · Mathematics 2014-10-09 Colin Cooper , Alan Frieze

Random walks have been intensively studied on regular and complex networks, which are used to represent pairwise interactions. Nonetheless, recent works have demonstrated that many real-world processes are better captured by higher-order…

Physics and Society · Physics 2023-06-19 Pietro Traversa , Guilherme Ferraz de Arruda , Yamir Moreno

Discrete quantum walks are dynamical protocols for controlling a single quantum particle. Despite of its simplicity, quantum walks display rich topological phenomena and provide one of the simplest systems to study and understand…

Quantum Physics · Physics 2011-12-09 Takuya Kitagawa

Deterministic walks over a random set of points in one and two dimensions (d=1,2) are considered. Points (``cities'') are randomly scattered in R^d following a uniform distribution. A walker (a ``tourist''), at each time step, goes to the…

Disordered Systems and Neural Networks · Physics 2016-08-31 Gilson F. Lima , Alexandre S. Martinez , Osame Kinouchi

A particle subject to successive, random displacements is said to execute a random walk (in position or some other coordinate). The mathematical properties of random walks have been very thoroughly investigated, and the model is used in…

Statistical Mechanics · Physics 2007-05-23 M. Wilkinson , B. Mehlig

Increased attention has been paid over the last four years to dynamic network embedding. Existing dynamic embedding methods, however, consider the problem as limited to the evolution of a topology over a sequence of global, discrete states.…

Machine Learning · Computer Science 2021-11-23 David Bayani