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Markovian evolving graphs are dynamic-graph models where the links among a fixed set of nodes change during time according to an arbitrary Markovian rule. They are extremely general and they can well describe important dynamic-network…

Discrete Mathematics · Computer Science 2011-03-04 Andrea Clementi , Angelo Monti , Francesco Pasquale , Riccardo Silvestri

We analyze the quantum entanglement properties of bosonic particles hopping over graph structures.Mode-entanglement of a graph vertex with respect the rest of the graph is generated, starting from a product state, by turning on for a finite…

Quantum Physics · Physics 2009-11-10 Paolo Giorda , Paolo Zanardi

In a recent Letter, Yang et al. [Phys. Rev. Lett. 109, 258701 (2012)] introduced the concept of observability transitions: the percolation-like emergence of a macroscopic observable component in graphs in which the state of a fraction of…

Statistical Mechanics · Physics 2014-02-11 Antoine Allard , Laurent Hébert-Dufresne , Jean-Gabriel Young , Louis J. Dubé

We introduce an extension of the frog model to Euclidean space and prove properties for the spread of active particles. Fix $r>0$ and place a particle at each point $x$ of a unit intensity Poisson point process $\mathcal P \subseteq \mathbb…

Probability · Mathematics 2019-01-31 Erin Beckman , Emily Dinan , Rick Durrett , Ran Huo , Matthew Junge

We introduce a continuum percolation model defined on the points of a d-dimensional homogeneous Poisson process. Each Poisson point is connected to all points within its connection range, which depends on the distances to the other Poisson…

Probability · Mathematics 2007-05-23 A. Gillett , M. Nuyens

We continue the study of infinite geodesics in planar first-passage percolation, pioneered by Newman in the mid 1990s. Building on more recent work of Hoffman, and Damron and Hanson, we develop an ergodic theory for infinite geodesics via…

Probability · Mathematics 2019-07-19 Daniel Ahlberg , Christopher Hoffman

This paper deals with the problem of detecting non-isotropic high-dimensional geometric structure in random graphs. Namely, we study a model of a random geometric graph in which vertices correspond to points generated randomly and…

Statistics Theory · Mathematics 2020-02-25 Ronen Eldan , Dan Mikulincer

We consider the detection of activations over graphs under Gaussian noise, where signals are piece-wise constant over the graph. Despite the wide applicability of such a detection algorithm, there has been little success in the development…

Machine Learning · Statistics 2012-07-13 James Sharpnack , Akshay Krishnamurthy , Aarti Singh

In this work, we study the problem of dispersion of mobile robots on dynamic rings. The problem of dispersion of $n$ robots on an $n$ node graph, introduced by Augustine and Moses Jr. [1], requires robots to coordinate with each other and…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-10-17 Ankush Agarwalla , John Augustine , William K. Moses , Madhav Sankar K. , Arvind Krishna Sridhar

We present a novel framework based on optimal transport for the challenging problem of comparing graphs. Specifically, we exploit the probabilistic distribution of smooth graph signals defined with respect to the graph topology. This allows…

Machine Learning · Computer Science 2019-12-09 Hermina Petric Maretic , Mireille EL Gheche , Giovanni Chierchia , Pascal Frossard

We propose a probabilistic formulation that enables sequential detection of multiple change points in a network setting. We present a class of sequential detection rules for certain functionals of change points (minimum among a subset), and…

Statistics Theory · Mathematics 2012-07-09 Arash Ali Amini , XuanLong Nguyen

Continuous monitoring of the spatio-temporal dynamic behavior of critical infrastructure networks, such as the power systems, is a challenging but important task. In particular, accurate and timely prediction of the (electro-mechanical)…

Systems and Control · Electrical Eng. & Systems 2022-02-17 Sai Pushpak Nandanoori , Sheng Guan , Soumya Kundu , Seemita Pal , Khushbu Agarwal , Yinghui Wu , Sutanay Choudhury

We consider random walks on dynamical networks where edges appear and disappear during finite time intervals. The process is grounded on three independent stochastic processes determining the walker's waiting-time, the up-time and down-time…

Physics and Society · Physics 2018-11-28 Julien Petit , Martin Gueuning , Timoteo Carletti , Ben Lauwens , Renaud Lambiotte

A Boolean network is a mapping $f :\{0,1\}^n \to \{0,1\}^n$, which can be used to model networks of $n$ interacting entities, each having a local Boolean state that evolves over time according to a deterministic function of the current…

Combinatorics · Mathematics 2021-04-29 Maximilien Gadouleau

A Poisson outdegree-one graph is an oriented graph based on a Poisson point process such that each vertex has only one outgoing edge. The paper focuses on the absence of percolation for such graphs. Our main result is based on two…

Probability · Mathematics 2019-05-03 David Coupier , David Dereudre , Simon Le Stum

Spatiotemporal graph represents a crucial data structure where the nodes and edges are embedded in a geometric space and can evolve dynamically over time. Nowadays, spatiotemporal graph data is becoming increasingly popular and important,…

Machine Learning · Computer Science 2022-03-02 Yuanqi Du , Xiaojie Guo , Hengning Cao , Yanfang Ye , Liang Zhao

In part III is realized the consistent development of Heisenberg--Dyson's two-layer matrix approximation to the graph formalism for postulating discrete physical objects (DPO) introduced in parts I-II in the form of discrete sets of…

General Physics · Physics 2007-05-23 V. E. Asribekov

In this work, percolation properties of device-to-device (D2D) networks in urban environments are investigated. The street system is modeled by a Poisson-Delaunay triangulation (PDT). Users are of two types: given either by a Cox process…

Probability · Mathematics 2024-02-14 David Corlin Marchand , David Coupier , Benoît Henry

We consider the problem of learning a graph from a finite set of noisy graph signal observations, the goal of which is to find a smooth representation of the graph signal. Such a problem is motivated by the desire to infer relational…

Machine Learning · Computer Science 2023-02-08 Xiaolu Wang , Yuen-Man Pun , Anthony Man-Cho So

A self-repelling random walk of a token on a graph is one in which at each step, the token moves to a neighbor that has been visited least often (with ties broken randomly). The properties of self-repelling random walks have been analyzed…

Networking and Internet Architecture · Computer Science 2017-08-24 Vinod Kulathumani , Masahiro Nakagawa , Anish Arora
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