| Full text | |
| Author(s): |
Martinez-Martinez, C. T.
[1, 2]
;
Mendez-Bermudez, J. A.
[2]
;
Peron, Thomas
[3]
;
Moreno, Yamir
[1, 4, 5]
Total Authors: 4
|
| Affiliation: | [1] Univ Zaragoza, Inst Biocomputat & Phys Complex Syst BIFI, Zaragoza 50018 - Spain
[2] Benemerita Univ Autonoma Puebla, Inst Fis, Apartado Postal J-48, Puebla 72570 - Mexico
[3] Univ Sao Paulo Sao Carlos, Inst Ciencias Matemat & Comp, BR-13566590 Sao Carlos, SP - Brazil
[4] Univ Zaragoza, Dept Theoret Phys, Zaragoza 50009 - Spain
[5] ISI Fdn, Turin - Italy
Total Affiliations: 5
|
| Document type: | Journal article |
| Source: | CHAOS SOLITONS & FRACTALS; v. 153, n. 2 DEC 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
Mutualistic networks are used to study the structure and processes inherent to mutualistic relationships. In this paper, we introduce a random matrix ensemble (RME) representing the adjacency matrices of mutualistic networks composed by two vertex sets of sizes n and m - n. Our RME depends on three parameters: the network size 11, the size of the smaller set m, and the connectivity between the two sets alpha, where alpha is the ratio of current adjacent pairs over the total number of possible adjacent pairs between the sets. We focus on the spectral, eigenvector and topological properties of the RME by computing, respectively, the ratio of consecutive eigenvalue spacings r, the Shannon entropy of the eigenvectors S, and the RandiC index R. First, within a random matrix theory approach (i.e. a statistical approach), we identify a parameter xi xi (n, m, alpha) that scales the average normalized measures < <(X)over bar> > (with X representing r, S and R). Specifically, we show that (i) xi proportional to alpha n with a weak dependence on m, and (ii) for xi < 1/10 most vertices in the mutualistic network are isolated, while for xi > 10 the network acquires the properties of a complete network, i.e., the transition from isolated vertices to a complete-like behavior occurs in the interval 1/10 < xi < 10. Then, we demonstrate that our statistical approach predicts reasonably well the properties of real-world mutualistic networks; that is, the universal curves < <(X)over bar> > vs. xi show good correspondence with the properties of real-world networks. (C) 2021 Elsevier Ltd. All rights reserved. (AU) | |
| FAPESP's process: | 16/23827-6 - Analysis of epidemic and synchronization processes in complex networks |
| Grantee: | Thomas Kaue Dal Maso Peron |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |