Multitarget search on complex networks: A logarithmic growth of global mean random cover time

Tongfeng Weng, Jie Zhang, Michael Small, Ji Yang, Farshid Hassani Bijarbooneh, Pan Hui

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

We investigate multitarget search on complex networks and derive an exact expression for the mean random cover time that quantifies the expected time a walker needs to visit multiple targets. Based on this, we recover and extend some interesting results of multitarget search on networks. Specifically, we observe the logarithmic increase of the global mean random cover time with the target number for a broad range of random search processes, including generic random walks, biased random walks, and maximal entropy random walks. We show that the logarithmic growth pattern is a universal feature of multi-target search on networks by using the annealed network approach and the Sherman-Morrison formula. Moreover, we find that for biased random walks, the global mean random cover time can be minimized, and that the corresponding optimal parameter also minimizes the global mean first passage time, pointing towards its robustness. Our findings further confirm that the logarithmic growth pattern is a universal law governing multitarget search in confined media.

Original languageEnglish
Article number093103
JournalChaos
Volume27
Issue number9
DOIs
Publication statusPublished - 1 Sep 2017

Fingerprint

Dive into the research topics of 'Multitarget search on complex networks: A logarithmic growth of global mean random cover time'. Together they form a unique fingerprint.

Cite this