# Burstiness and fractional diffusion on complex networks

@article{deNigris2016BurstinessAF, title={Burstiness and fractional diffusion on complex networks}, author={Sarah de Nigris and Anthony Hastir and Renaud Lambiotte}, journal={The European Physical Journal B}, year={2016}, volume={89}, pages={1-7} }

Abstract
Many dynamical processes on real world networks display complex temporal patterns as, for
instance, a fat-tailed distribution of inter-events times, leading to heterogeneous
waiting times between events. In this work, we focus on distributions whose average
inter-event time diverges, and study its impact on the dynamics of random walkers on
networks. The process can naturally be described, in the long time limit, in terms of
Riemann-Liouville fractional derivatives. We show that all…

## 11 Citations

### Continuous-Time Random Walks and Temporal Networks

- MathematicsComputational Social Sciences
- 2019

This chapter focuses on the mathematical modelling of diffusion on temporal networks, and on its connection with continuous-time random walks, and shows how different mechanisms tend to slow down the exploration of the network when the temporal distribution presents a fat tail.

### Random walks in non-Poissoinan activity driven temporal networks

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This work derives analytic expressions for the steady state occupation probability and first passage time distribution in the infinite network size and strong aging limits, showing that the random walk dynamics on non-Markovian networks are fundamentally different from what is observed in Markovian Networks.

### Random walks with long-range steps generated by functions of Laplacian matrices

- Mathematics
- 2017

In this paper, we explore different Markovian random walk strategies on networks with transition probabilities between nodes defined in terms of functions of the Laplacian matrix. We generalize…

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### Random walks on weighted networks: a survey of local and non-local dynamics

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A survey of different types of random walk models with local and non-local transitions on undirected weighted networks by defining the dynamics as a discrete-time Markovian process with transition probabilities expressed in terms of a symmetric matrix of weights.

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