k-core percolation on interdependent and interconnected multiplex networks
Kexian Zheng, Ying Liu, Yang Wang, Wei Wang

TL;DR
This paper analyzes the robustness of interdependent multiplex networks under k-core percolation, revealing complex phase transitions influenced by inter-layer coupling strength and network type, with theoretical and simulation validation.
Contribution
It introduces an analytical framework for k-core percolation on multiplex networks with interdependence and interconnected links, uncovering diverse phase transition behaviors.
Findings
Giant component size exhibits first- and second-order transitions depending on coupling strength.
System robustness increases with stronger dependency on initially robust networks.
Transition types differ between ER-ER and SF-SF multiplex networks under varying coupling conditions.
Abstract
Many real-world networks are coupled together to maintain their normal functions. Here we study the robustness of multiplex networks with interdependent and interconnected links under k-core percolation, where a node fails when it connects to a threshold of less than k neighbors. By deriving the self-consistency equations, we solve the key quantities of interests such as the critical threshold and size of the giant component analytically and validate the theoretical results with numerical simulations. We find a rich phase transition phenomenon as we tune the inter-layer coupling strength. Specifically speaking, in the ER-ER multiplex networks, with the increase of coupling strength, the size of the giant component in each layer first undergoes a first-order transition and then a second-order transition and finally a first-order transition. This is due to the nature of inter-layer links…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
