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Reconstruction of complex networks from causal information

Grant number: 18/12072-0
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): December 01, 2018
Status:Discontinued
Field of knowledge:Physical Sciences and Mathematics - Physics
Principal researcher:Francisco Aparecido Rodrigues
Grantee:Tiago Martinelli
Home Institution: Instituto de Física de São Carlos (IFSC). 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):20/04543-2 - Causal reasoning and decision-making processes, BE.EP.DR

Abstract

One of the main questions in the study of complex systems is to understand how their organization, represented by complex networks, influences dynamic processes. For example, how patterns of connections between coupled oscillators influence the emergence of the synchronous state. Although this study is fundamental for developing methods to control a dynamic process from changes in the structure of the network, in practice the only available information is the time series of a given dynamic process unknown a priori. Recent advances show the possibility of recovering emergent properties of the network from data. Therefore, the objective of this project will be the reconstruction of complex networks from the analysis of available information. In other words, from a time series we can reverse the causal order to obtain the model via data. Such a study will allow a better understanding of these processes and their topology behind, enabling improvements in planning to deal, for example, with degenerative diseases. (AU)

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