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Exact sampling of graphs with prescribed degree correlations
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Bassler, Kevin E., Del Genio, Charo I., Erdős, Péter L., Miklós, István and Toroczkai, Zoltán (2015) Exact sampling of graphs with prescribed degree correlations. New Journal of Physics, 17 (8). 083052. doi:10.1088/1367-2630/17/8/083052 ISSN 1367-2630.
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Official URL: http://dx.doi.org/10.1088/1367-2630/17/8/083052
Abstract
Many real-world networks exhibit correlations between the node degrees. For instance, in social networks nodes tend to connect to nodes of similar degree and conversely, in biological and technological networks, high-degree nodes tend to be linked with low-degree nodes. Degree correlations also affect the dynamics of processes supported by a network structure, such as the spread of opinions or epidemics. The proper modelling of these systems, i.e., without uncontrolled biases, requires the sampling of networks with a specified set of constraints. We present a solution to the sampling problem when the constraints imposed are the degree correlations. In particular, we develop an exact method to construct and sample graphs with a specified joint-degree matrix, which is a matrix providing the number of edges between all the sets of nodes of a given degree, for all degrees, thus completely specifying all pairwise degree correlations, and additionally, the degree sequence itself. Our algorithm always produces independent samples without backtracking. The complexity of the graph construction algorithm is ${\mathcal{O}}({NM})$ where N is the number of nodes and M is the number of edges.
Item Type: | Journal Article | ||||||||
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Subjects: | Q Science > QA Mathematics T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Research Centres > Centre for Complexity Science Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) Faculty of Science, Engineering and Medicine > Science > Mathematics Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School |
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Library of Congress Subject Headings (LCSH): | Computer networks, Graph algorithms, Markov processes, Monte Carlo method | ||||||||
Journal or Publication Title: | New Journal of Physics | ||||||||
Publisher: | IOP Publishing | ||||||||
ISSN: | 1367-2630 | ||||||||
Official Date: | 26 August 2015 | ||||||||
Dates: |
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Volume: | 17 | ||||||||
Number: | 8 | ||||||||
Article Number: | 083052 | ||||||||
DOI: | 10.1088/1367-2630/17/8/083052 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 18 November 2016 | ||||||||
Date of first compliant Open Access: | 21 November 2016 | ||||||||
Funder: | United States. Air Force. Office of Scientific Research (AFOSR), United States. Defense Advanced Research Projects Agency (DARPA), National Science Foundation (U.S.) (NSF), Seventh Framework Programme (European Commission) (FP7), United States. Defense Threat Reduction Agency (DTRA) | ||||||||
Grant number: | FA9550-12-1-0405 (AFOSR/DARPA), DMR-1206839 (NSF), 288021 (FP7), HDTRA-1-09-1-0039 (DTRA) |
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