- Abstract:
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We analyze a collection of empirical networks in a wide spectrum of disciplines and show that strong non-normality is ubiquitous in network science. Dynamical processes evolving on non-normal networks exhibit a peculiar behavior, as initial small disturbances may undergo a transient phase and be strongly amplified in linearly stable systems. In addition, eigenvalues may become extremely sensible to noise and have a diminished physical meaning. We identify structural properties of networks tha...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Publisher's Version
- Files:
-
-
(pdf, 815.1KB)
-
- Publisher copy:
- 10.1126/sciadv.aau9403
-
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- Publisher:
- American Association for the Advancement of Science Publisher's website
- Journal:
- Science Advances Journal website
- Volume:
- 4
- Issue:
- 12
- Pages:
- eaau9403
- Publication date:
- 2018-12-12
- Acceptance date:
- 2018-11-14
- DOI:
- EISSN:
-
2375-2548
- Pubs id:
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pubs:942612
- URN:
-
uri:e18fcce0-131c-4df7-89cb-5b017f8ee0bf
- UUID:
-
uuid:e18fcce0-131c-4df7-89cb-5b017f8ee0bf
- Local pid:
- pubs:942612
- Copyright holder:
- Asllani et al.
- Copyright date:
- 2018
- Notes:
- Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC)
Journal article
Structure and dynamical behavior of non-normal networks
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