Forecasting transitions in systems with high-dimensional stochastic complex dynamics: A linear stability analysis of the tangled nature model
File(s)1407.5024v2.pdf (4.29 MB)
Accepted version
Author(s)
Cairoli, A
Piovani, D
Jensen, HJ
Type
Journal Article
Abstract
We propose a new procedure to monitor and forecast the onset of transitions in high-dimensional complex systems. We describe our procedure by an application to the tangled nature model of evolutionary ecology. The quasistable configurations of the full stochastic dynamics are taken as input for a stability analysis by means of the deterministic mean-field equations. Numerical analysis of the high-dimensional stability matrix allows us to identify unstable directions associated with eigenvalues with a positive real part. The overlap of the instantaneous configuration vector of the full stochastic system with the eigenvectors of the unstable directions of the deterministic mean-field approximation is found to be a good early warning of the transitions occurring intermittently.
Date Issued
2014-12-31
Date Acceptance
2014-12-24
Citation
Physical Review Letters, 2014, 113 (26)
ISSN
0031-9007
Publisher
American Physical Society
Journal / Book Title
Physical Review Letters
Volume
113
Issue
26
Copyright Statement
© 2014 The American Physical Society
Subjects
Science & Technology
Physical Sciences
Physics, Multidisciplinary
Physics
Publication Status
Published
Article Number
264102
Date Publish Online
2014-12-24