English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Universality in spectral condensation

Pavithran, I., Unni, V. R., Varghese, A. J., Premraj, D., Sujith, R. I., Vijayan, C., Saha, A., Marwan, N., Kurths, J. (2020): Universality in spectral condensation. - Scientific Reports, 10, 17405.
https://doi.org/10.1038/s41598-020-73956-7

Item is

Files

show Files
hide Files
:
24990oa.pdf (Publisher version), 3MB
Name:
24990oa.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-

Locators

show

Creators

show
hide
 Creators:
Pavithran, Induja1, Author
Unni, Vishnu R.1, Author
Varghese, Alan J.1, Author
Premraj, D.1, Author
Sujith, R. I.1, Author
Vijayan, C.1, Author
Saha, Abhishek1, Author
Marwan, Norbert2, Author              
Kurths, Jürgen2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Content

show
hide
Free keywords: -
 Abstract: Self-organization is the spontaneous formation of spatial, temporal, or spatiotemporal patterns in complex systems far from equilibrium. During such self-organization, energy distributed in a broadband of frequencies gets condensed into a dominant mode, analogous to a condensation phenomenon. We call this phenomenon spectral condensation and study its occurrence in fluid mechanical, optical and electronic systems. We define a set of spectral measures to quantify this condensation spanning several dynamical systems. Further, we uncover an inverse power law behaviour of spectral measures with the power corresponding to the dominant peak in the power spectrum in all the aforementioned systems.

Details

show
hide
Language(s):
 Dates: 2020-10-152020-10-15
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41598-020-73956-7
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Research topic keyword: Nonlinear Dynamics
Model / method: Nonlinear Data Analysis
Organisational keyword: RD4 - Complexity Science
Working Group: Development of advanced time series analysis techniques
Working Group: Network- and machine-learning-based prediction of extreme events
OATYPE: Gold - DEAL Springer Nature
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Scientific Reports
Source Genre: Journal, SCI, Scopus, p3, OA
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 10 Sequence Number: 17405 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals2_395
Publisher: Nature