Synchronization of frustrated Kuramoto oscillators on modular networks
Study of phase synchronization in oscillators networks and applications to informa...
| Grant number: | 16/23827-6 |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| Effective date (Start): | August 01, 2017 |
| Effective date (End): | June 19, 2022 |
| Field of knowledge: | Physical Sciences and Mathematics - Physics |
| Principal Investigator: | Francisco Aparecido Rodrigues |
| Grantee: | Thomas Kaue Dal Maso Peron |
| Host Institution: | Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil |
| Associated research grant: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry, AP.CEPID |
| Associated scholarship(s): | 18/15589-3 - Dynamical Processes on Ecological Networks, BE.EP.PD |
Abstract The field we know today as Network Science had its beginning in the analysis of large database setswith the initial goal in mapping the connectivity pattern of real complex systems. The great finding ofthe early works in this context was the discovery that systems of different nature exhibited highly nontrivialstructural patterns, such as the emergence of scale-free properties and hierarchical organizations ofits elements. These results were then followed by countless works focused in the development and formalizationof metrics devoted to the structural characterization of these systems. However, in many cases, thetopological description of a given system does not provide all resources to thoroughly assess the system'sevolution. Once the structure has been quantified, one still needs to establish the connection between thenetwork topology and dynamical processes taking place on it. Unfortunately, progress in this directionturned out to be much more slower than in the structural characterization of networks. Indeed, analyticalresults concerning dynamical processes in these structures are hard, or even impossible, to be obtained;especially in topologies that present characteristics found in real networks. It is in this context that lies themotivation of this project, namely to study dynamical processes in complex networks that exhibit topologiesakin to the ones observed in real systems. To this end, we will study epidemic and synchronizationprocesses considering random graph models that generate networks that incorporate structural propertiesobserved empirically. With this approach, we aim at quantifying the influence of topological patternsusually neglected on the dynamics of real complex systems. Finally, the analysis developed firstly for randommodels will be later applied to the study of real-world networks whose functioning is described bythe dynamical processes under investigation in the project, such as power-grid networks in the context ofsynchronization, and social networks under the influence of endemic and rumour spreading processes. | |
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