The Experts below are selected from a list of 4026 Experts worldwide ranked by ideXlab platform
Wang Wei - One of the best experts on this subject based on the ideXlab platform.
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k-core percolation on interdependent and interconnected multiplex Networks
2021Co-Authors: Zheng Kexian, Liu Ying, Wang Yang, Wang WeiAbstract: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 with both connectivity and dependency simultaneously. The system is more robust if the dependency on the initial robust Network is strong and more vulnerable if the dependency on the initial Attacked Network is strong. These effects are even amplified in the cascading process. When applying our model to the SF-SF multiplex Networks, the type of transition changes. The system undergoes a first-order phase transition first only when the two layers' mutually coupling is very strong and a second-order transition in other conditions.Comment: 8 pages,7 figure
Wei Wang - One of the best experts on this subject based on the ideXlab platform.
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k-core percolation on interdependent and interconnected multiplex Networks
'IOP Publishing', 2021Co-Authors: Kexian Zheng, Ying Liu, Yang Wang, Wei WangAbstract: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 less than k neighbors. By deriving the self-consistent equations, we solve the key quantities of interests such as the critical threshold and size of the giant component and validate the theoretical predictions by 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 with both connectivity and dependency. The system is more robust if the dependency on the initially robust Network is strong and more vulnerable if the dependency on the initial Attacked Network is strong. These effects are even amplified in the cascading process. When applying our model to the SF-SF multiplex Networks, the type of transition changes. The system undergoes a first-order phase transition first only when the two layers' mutually coupling is very strong and a second-order transition in all other conditions
Zheng Kexian - One of the best experts on this subject based on the ideXlab platform.
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k-core percolation on interdependent and interconnected multiplex Networks
2021Co-Authors: Zheng Kexian, Liu Ying, Wang Yang, Wang WeiAbstract: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 with both connectivity and dependency simultaneously. The system is more robust if the dependency on the initial robust Network is strong and more vulnerable if the dependency on the initial Attacked Network is strong. These effects are even amplified in the cascading process. When applying our model to the SF-SF multiplex Networks, the type of transition changes. The system undergoes a first-order phase transition first only when the two layers' mutually coupling is very strong and a second-order transition in other conditions.Comment: 8 pages,7 figure
Kexian Zheng - One of the best experts on this subject based on the ideXlab platform.
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k-core percolation on interdependent and interconnected multiplex Networks
'IOP Publishing', 2021Co-Authors: Kexian Zheng, Ying Liu, Yang Wang, Wei WangAbstract: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 less than k neighbors. By deriving the self-consistent equations, we solve the key quantities of interests such as the critical threshold and size of the giant component and validate the theoretical predictions by 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 with both connectivity and dependency. The system is more robust if the dependency on the initially robust Network is strong and more vulnerable if the dependency on the initial Attacked Network is strong. These effects are even amplified in the cascading process. When applying our model to the SF-SF multiplex Networks, the type of transition changes. The system undergoes a first-order phase transition first only when the two layers' mutually coupling is very strong and a second-order transition in all other conditions
Liu Ying - One of the best experts on this subject based on the ideXlab platform.
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k-core percolation on interdependent and interconnected multiplex Networks
2021Co-Authors: Zheng Kexian, Liu Ying, Wang Yang, Wang WeiAbstract: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 with both connectivity and dependency simultaneously. The system is more robust if the dependency on the initial robust Network is strong and more vulnerable if the dependency on the initial Attacked Network is strong. These effects are even amplified in the cascading process. When applying our model to the SF-SF multiplex Networks, the type of transition changes. The system undergoes a first-order phase transition first only when the two layers' mutually coupling is very strong and a second-order transition in other conditions.Comment: 8 pages,7 figure