Structural and temporal heterogeneities on networks

A heterogeneous continuous time random walk is an analytical formalism for studying and modeling diffusion processes in heterogeneous structures on microscopic and macroscopic scales. In this paper we study both analytically and numerically the effects of structural and temporal heterogeneities onto the diffusive dynamics on different types of networks. For this purpose we investigate how the distribution of the first passage time is affected by the global topological network properties and heterogeneities in the distributions of the travel times. In particular, we analyze transport properties of random networks and define network measures based on the first-passage characteristics. The heterogeneous continuous time random walk framework, presented in the paper, has potential applications in biology, social and urban science, search of optimal transport properties, analysis of the effects of heterogeneities or bursts in transportation networks.

[1]  A. Godec,et al.  First passage time distribution in heterogeneity controlled kinetics: going beyond the mean first passage time , 2015, Scientific Reports.

[2]  M. Weigt,et al.  On the properties of small-world network models , 1999, cond-mat/9903411.

[3]  Mason A. Porter,et al.  Tie-decay temporal networks in continuous time and eigenvector-based centralities , 2018, ArXiv.

[4]  T. Geisel,et al.  The scaling laws of human travel , 2006, Nature.

[5]  H. Stanley,et al.  Territory covered by N diffusing particles , 1992, Nature.

[6]  I. Procaccia,et al.  Analytical solutions for diffusion on fractal objects. , 1985, Physical review letters.

[7]  Timoteo Carletti,et al.  Random walk on temporal networks with lasting edges , 2018, Physical Review E.

[8]  Erik M. Bollt,et al.  What is Special about Diffusion on Scale-Free Nets? , 2004 .

[9]  Z. Schuss,et al.  Narrow Escape, Part II: The Circular Disk , 2004, math-ph/0412050.

[10]  Cohen,et al.  Resilience of the internet to random breakdowns , 2000, Physical review letters.

[11]  Lev Muchnik,et al.  Identifying influential spreaders in complex networks , 2010, 1001.5285.

[12]  Maksim Kitsak,et al.  Identifying influential spreaders in complex networks , 2010 .

[13]  Alexander Blumen,et al.  Generalized Vicsek Fractals: Regular Hyperbranched Polymers , 2004 .

[14]  Distribution of shortest path lengths in a class of node duplication network models. , 2017, Physical review. E.

[15]  Jari Saramäki,et al.  Exploring temporal networks with greedy walks , 2015, ArXiv.

[16]  Zhongzhi Zhang,et al.  Laplacian spectra of a class of small-world networks and their applications , 2015, Scientific Reports.

[17]  S. Redner,et al.  A Kinetic View of Statistical Physics , 2010 .

[18]  Albert-László Barabási,et al.  Evolution of Networks: From Biological Nets to the Internet and WWW , 2004 .

[19]  Dirk Brockmann,et al.  Cover time for random walks on arbitrary complex networks , 2017, Physical review. E.

[20]  R. Metzler,et al.  Towards a full quantitative description of single-molecule reaction kinetics in biological cells. , 2018, Physical chemistry chemical physics : PCCP.

[21]  U. Feige,et al.  Spectral Graph Theory , 2015 .

[22]  Michael Batty,et al.  A long-time limit of world subway networks , 2011, 1105.5294.

[23]  S. N. Dorogovtsev,et al.  Evolution of networks , 2001, cond-mat/0106144.

[24]  M. Newman,et al.  Mean-field solution of the small-world network model. , 1999, Physical review letters.

[25]  Remco van der Hofstad,et al.  Random Graphs and Complex Networks , 2016, Cambridge Series in Statistical and Probabilistic Mathematics.

[26]  Jean-Charles Delvenne,et al.  Burstiness and spreading on temporal networks , 2013, ArXiv.

[27]  Jennifer M. Larson The weakness of weak ties for novel information diffusion , 2017, Applied Network Science.

[28]  M. Dolgushev,et al.  Dynamics of Semiflexible Chains, Stars, and Dendrimers , 2009 .

[29]  Sidney Redner,et al.  A guide to first-passage processes , 2001 .

[30]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[31]  Jean-Charles Delvenne,et al.  The many facets of community detection in complex networks , 2016, Applied Network Science.

[32]  S. Redner,et al.  First-passage properties of the Erdos Renyi random graph , 2004, cond-mat/0410309.

[33]  Gaël Beaunée,et al.  Dynamical network models for cattle trade: towards economy-based epidemic risk assessment , 2017, J. Complex Networks.

[34]  A. Talbot The Accurate Numerical Inversion of Laplace Transforms , 1979 .

[35]  B Kahng,et al.  First passage time for random walks in heterogeneous networks. , 2012, Physical review letters.

[36]  D. Brockmann,et al.  Effective distances for epidemics spreading on complex networks , 2016, Physical review. E.

[37]  J. Stoyanov A Guide to First‐passage Processes , 2003 .

[38]  Michele Re Fiorentin,et al.  Epidemic Threshold in Continuous-Time Evolving Networks , 2017, Physical review letters.

[39]  Daniel S. Fisher,et al.  Random walks in random environments , 1984 .

[40]  Liubov Tupikina,et al.  Heterogeneous continuous-time random walks. , 2017, Physical review. E.

[41]  E. Agliari,et al.  Random walks on deterministic scale-free networks: exact results. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[42]  Bin Wu,et al.  Eigenvalues of normalized Laplacian matrices of fractal trees and dendrimers: analytical results and applications. , 2013, The Journal of chemical physics.

[43]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[44]  Renaud Lambiotte,et al.  Diffusion on networked systems is a question of time or structure , 2013, Nature Communications.

[45]  Romualdo Pastor-Satorras,et al.  Random walks on temporal networks. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[46]  Piet Van Mieghem,et al.  Graph Spectra for Complex Networks , 2010 .

[47]  Paolo Boldi,et al.  Estimating latent feature-feature interactions in large feature-rich graphs , 2016, Internet Math..

[48]  F Jasch,et al.  Trapping of random walks on small-world networks. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[49]  D. S. Grebenkov,et al.  First exit times of harmonically trapped particles: a didactic review , 2014, 1411.3598.

[50]  S. Havlin,et al.  Scaling theory of transport in complex biological networks , 2007, Proceedings of the National Academy of Sciences.

[51]  J. Klafter,et al.  First Steps in Random Walks: From Tools to Applications , 2011 .

[52]  Marc Barthelemy,et al.  Spatial Networks , 2010, Encyclopedia of Social Network Analysis and Mining.

[53]  E. Montroll,et al.  Random Walks on Lattices. II , 1965 .

[54]  J. Quastel Diffusion in Disordered Media , 1996 .

[55]  F. Chung,et al.  Connected Components in Random Graphs with Given Expected Degree Sequences , 2002 .