Document detail
ID
oai:arXiv.org:2403.12560
Topic
Condensed Matter - Statistical Mec... Computer Science - Social and Info... Physics - Physics and Society 60J27Author
Awolude, O. S. Cator, E. Don, H.Category
Computer Science
Year
2024
listing date
7/17/2024
Keywords
graphs sparseAbstract
There are many methods to estimate the quasi-stationary infected fraction of the SIS process on (random) graphs.
A challenge is to adequately incorporate correlations, which is especially important in sparse graphs.
Methods typically are either significantly biased in sparse graphs, or computationally very demanding already for small network sizes.
In this paper we present a new method to determine the infected fraction in sparse graphs, which we test on Erd\H{o}s-R\'enyi graphs.
Our method does take into account correlations and gives accurate predictions.
At the same time, computations are very feasible and can easily be done even for large networks.
;Comment: 44 pages, 22 figures
Awolude, O. S.,Cator, E.,Don, H., 2024, The SIS process on Erd\"os-R\'enyi graphs: determining the infected fraction
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