Regensburg 2019 – wissenschaftliches Programm
SOE 6.5: Vortrag
Montag, 1. April 2019, 16:00–16:15, H20
Principal Eigenvector Localization in Multilayer Networks — •Priodyuti Pradhan1 and Sarika Jalan1,2 — 1Complex Systems Lab, Discipline of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore-453552, India — 2Centre for Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore-453552, India
Starting with a multilayer network (MN) corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired MN becomes more localized. The localization of an eigenvector refers to a state where few components of the vector take very high values, and rest of the components take very small values. For a two layers MN, the optimization process can be implemented in two different edge rewiring protocols; (1) by rewiring edges in both-layers or (2) by rewiring edges in only one layer. We reveal that for both the rewiring protocols, though there is an emergence of various specific structural features, the different rewiring protocols lead to a noticeable difference in the spectral properties of the optimized MN. For the both-layers rewiring protocol, PEV is sensitive to a single edge rewiring in the optimized MN, and however, interestingly, we get rid of this sensitivity of PEV for the single-layer rewiring protocol. This sensitivity in the localization behavior of PEV is accompanied by the second largest eigenvalue lying very close to the largest one. Furthermore, analysis of MNs constructed using real-world social and biological data show a good agreement with the simulation results for model MN.