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Physics, Fluids & Plasmas
Fei Ma, Ping Wang
Summary: The study proposes a simple algorithmic framework for generating power-law graphs with small diameters and examines their structural properties. The results show that these graphs have unique features such as density characteristics and higher trapping efficiency compared to existing scale-free models, confirmed through extensive simulations.
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Physics, Fluids & Plasmas
Fernanda H. Gonzalez, Alejandro P. Riascos, Denis Boyer
Summary: The study focuses on diffusive transport of Markovian random walks on networks with stochastic resetting to multiple nodes. Analytical expressions for stationary occupation probability, mean, and global first passage times are derived to characterize the effect of resetting on random walk strategies. The methods are applied to various dynamics, including Levy flights and Google random walk strategy.
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Mathematics, Interdisciplinary Applications
Changming Xing, Hao Yuan
Summary: Lazy random walks in a pseudofractal scale-free web, considering self-loop jumps on graph vertices, are studied in this paper. The exact formulas for the average trapping time (ATT) in the trapping problem with one fixed trap at a hub node are derived using two different methods. The coefficient of the ATT formula is affected by the walking rule with self-loop jumps, but the leading scaling of the trapping efficiency remains unchanged.
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY
(2022)
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Multidisciplinary Sciences
Alexandre Bovet, Jean-Charles Delvenne, Renaud Lambiotte
Summary: This article introduces a method based on a dynamical process evolving on a temporal network, which uncovers different dynamic scales in a system by considering the ordering of edges in forward and backward time. The method provides a new approach to extracting a simplified view of time-dependent network interactions in a system.
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Engineering, Multidisciplinary
Qiang Wang, Hao Jiang, Ying Jiang, Shuwen Yi, Lixia Li, Cong-Cong Xing, Jun Huang
Summary: This paper investigates the study of multiple disjoint shortest paths (MDSP) in complex networks. The authors model and analyze the MDSP problem per hyperbolic random graphs, and propose an algorithm for searching MDSP on the network navigation skeleton in a hyperbolic space. Experimental results show that the algorithm guarantees the success of MDSP searching and achieves significant gains in terms of running time.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Multidisciplinary Sciences
Alexander Ponomarenko, Leonidas Pitsoulis, Marat Shamshetdinov
Summary: The LPAM method introduces a new approach for detecting overlapping communities in networks, considering different distance functions and evaluating its performance on real life instances and synthetic network benchmarks. It utilizes link partitioning and partitioning around medoids to detect overlapping communities in graphs.
Article
Business
Alberto Arcagni, Rosanna Grassi, Silvana Stefani, Anna Torriero
Summary: Assortativity by degree in complex networks is quantified by the Newman coefficient, indicating a tendency for nodes to be connected to others with a similar degree. This study proposes a new class of higher-order assortativity measures for weighted networks, showing effectiveness in social networks. Applications to Facebook and co-authorship networks analyze assortativity beyond nearest neighbors.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Physics, Fluids & Plasmas
Feng Huang, Hanshuang Chen
Summary: This study investigates discrete-time random walks with first-passage resetting processes on arbitrary networks, deriving exact expressions for stationary occupation probability, average number of resets, and mean first-passage time. Results show that these quantities can be expressed in terms of the fundamental matrix, demonstrating the advantage of first-passage resetting in global search on various networks.
Article
Evolutionary Biology
Alexander A. Fisher, Xiang Ji, Zhenyu Zhang, Philippe Lemey, Marc A. Suchard
Summary: Relaxed random walk (RRW) models introduce branch-specific rate multipliers to modulate the variance of a standard Brownian diffusion process to accurately model overdispersed biological data. A scalable method in a Bayesian framework is presented to efficiently fit RRWs and infer branch-specific variation. The Hamiltonian Monte Carlo sampler approximates the high-dimensional posterior and achieves computational complexity that scales linearly with the number of taxa studied.
SYSTEMATIC BIOLOGY
(2021)
Article
Physics, Multidisciplinary
Alejandro P. Riascos, Francisco Hernandez Padilla
Summary: In this paper, a framework for comparing differences in occupation probabilities of two random walk processes on networks is presented. The framework considers modifications of the network or the transition probabilities between nodes. A dissimilarity measure is defined using the eigenvalues and eigenvectors of the normalized Laplacian. The framework is used to examine differences in diffusive dynamics, the effect of new edges and rewiring in networks, and divergences in transport in degree-biased random walks and random walks with stochastic reset.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2023)
Article
Physics, Fluids & Plasmas
Yating Wang, Hanshuang Chen
Summary: In this paper, the authors investigate the effects of stochastic resetting on the entropy rate of discrete-time Markovian processes. The study reveals nontrivial and interesting features of stochastic dynamics, showing a nonmonotonic dependence of the entropy rate on the resetting probability. The research also explores the mixing properties of stochastic processes on different network topologies.
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Computer Science, Software Engineering
John Fernley, Marcel Ortgiese
Summary: The voter model is analyzed in the context of a subcritical scale-free random graph, considering the time to consensus and the influence of a temperature parameter. The interplay between temperature and graph structure leads to a rich phase diagram that dominates the time to consensus. Additionally, a discursive voter model, where voters discuss opinions with neighbors, is also considered.
RANDOM STRUCTURES & ALGORITHMS
(2023)
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Mathematics, Interdisciplinary Applications
Long Gao, Junhao Peng, Chunming Tang
Summary: The study focused on the first-passage process on fractal scale-free trees, examining the impact of the time to reach the target site on network transport efficiency. By introducing proper weights and the parameter w, the process was accelerated, and a method to find the minimum GMFPT was presented.
FRACTAL AND FRACTIONAL
(2021)
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Physics, Fluids & Plasmas
Hanshuang Chen, Yanfei Ye
Summary: This study investigates discrete-time random walks on networks subject to time-dependent stochastic resetting. The results demonstrate that time-modulated resetting protocols can be more advantageous in accelerating the completion of a target search process compared to constant-probability resetting.
Article
Physics, Multidisciplinary
Kiril Zelenkovski, Trifce Sandev, Ralf Metzler, Ljupco Kocarev, Lasko Basnarkov
Summary: We present a refined approach to explore complex networks with stochastic resetting based on node centrality measures. This approach allows a random walker to jump not only to a deliberately chosen resetting node, but also to a node that can reach all other nodes faster. By considering the resetting site as the geometric center, we calculate the Global Mean First Passage Time (GMFPT) using Markov chain theory to determine the search performance of the random walk with resetting. We compare different nodes as resetting sites by comparing their GMFPT values.
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Computer Science, Hardware & Architecture
Yuan Lin, Zhongzhi Zhang
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Automation & Control Systems
Yi Qi, Zhongzhi Zhang, Yuhao Yi, Huan Li
IEEE TRANSACTIONS ON CYBERNETICS
(2019)
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Computer Science, Hardware & Architecture
Yi Qi, Yuhao Yi, Zhongzhi Zhang
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Computer Science, Theory & Methods
Yucheng Wang, Qi Bao, Zhongzhi Zhang
THEORETICAL COMPUTER SCIENCE
(2019)
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Computer Science, Information Systems
Yibin Sheng, Zhongzhi Zhang
IEEE TRANSACTIONS ON INFORMATION THEORY
(2019)
Article
Computer Science, Information Systems
Huan Li, Stacy Patterson, Yuhao Yi, Zhongzhi Zhang
IEEE TRANSACTIONS ON INFORMATION THEORY
(2020)
Article
Automation & Control Systems
Yuhao Yi, Zhongzhi Zhang, Stacy Patterson
IEEE TRANSACTIONS ON CYBERNETICS
(2020)
Proceedings Paper
Computer Science, Theory & Methods
Zuobai Zhang, Wanyue Xu, Zhongzhi Zhang
PROCEEDINGS OF THE 13TH INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING (WSDM '20)
(2020)
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Computer Science, Hardware & Architecture
Yuan Lin, Zhongzhi Zhang
Proceedings Paper
Computer Science, Artificial Intelligence
Yujia Jin, Qi Bao, Zhongzhi Zhang
2019 19TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM 2019)
(2019)
Proceedings Paper
Computer Science, Theory & Methods
Huan Li, Richard Peng, Liren Shan, Yuhao Yi, Zhongzhi Zhang
WEB CONFERENCE 2019: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW 2019)
(2019)
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Engineering, Multidisciplinary
Yi Qi, Zhongzhi Zhang
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2019)
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Automation & Control Systems
Stacy Patterson, Yuhao Yi, Zhongzhi Zhang
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2019)
Proceedings Paper
Computer Science, Theory & Methods
Huan Li, Zhongzhi Zhang
SODA'18: PROCEEDINGS OF THE TWENTY-NINTH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS
(2018)
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Computer Science, Hardware & Architecture
Yi Qi, Huan Li, Zhongzhi Zhang