Imperial College London
Alternate

ProfessorSebastianvan Strien

Faculty of Natural Sciences, Department of Mathematics

Chair in Dynamical Systems
 
 
 
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Contact

 

+44 (0)20 7594 2844s.van-strien Website

 
 
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Location

 

6M36Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Eroglu:2020:10.1103/PhysRevX.10.021047,
author = {Eroglu, D and Tanzi, M and van, Strien S and Pereira, T},
doi = {10.1103/PhysRevX.10.021047},
journal = {Physical Review X},
title = {Revealing dynamics, communities and criticality from data},
url = {http://dx.doi.org/10.1103/PhysRevX.10.021047},
volume = {10},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Complex systems such as ecological communities and neuron networks are essential parts of our everyday lives. These systems are composed of units which interact through intricate networks. The ability to predict sudden changes in the dynamics of these networks, known as critical transitions, from data is important to avert disastrous consequences of major disruptions. Predicting such changes is a major challenge as it requires forecasting the behaviour for parameter ranges for which no data on the system is available. We address this issue for networks with weak individual interactions and chaotic local dynamics. We do this by building a model network, termed an {}, consisting of the underlying local dynamics and a statistical description of their interactions. We show that behaviour of such networks can be decomposed in terms of an emergent deterministic component and a {} term. Traditionally, such fluctuations are filtered out. However, as we show, they are key to accessing the interaction structure. { We illustrate this approach on synthetic time-series of realistic neuronal interaction networks of the cat cerebral cortex and on experimental multivariate data of optoelectronic oscillators. } We reconstruct the community structure by analysing the stochastic fluctuations generated by the network and predict critical transitions for coupling parameters outside the observed range.
AU  - Eroglu,D
AU  - Tanzi,M
AU  - van,Strien S
AU  - Pereira,T
DO  - 10.1103/PhysRevX.10.021047
PY  - 2020///
SN  - 2160-3308
TI  - Revealing dynamics, communities and criticality from data
T2  - Physical Review X
UR  - http://dx.doi.org/10.1103/PhysRevX.10.021047
UR  - https://journals.aps.org/prx/abstract/10.1103/PhysRevX.10.021047
UR  - http://hdl.handle.net/10044/1/79194
VL  - 10
ER  -
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