Investigation of complexity dynamics in a DC glow discharge magnetized plasma using recurrence quantification analysis

Vramori Mitra*, Bornali Sarma, Arun Sarma, M. S. Janaki, A. N. Sekar Iyengar, Norbert Marwan, Juergen Kurths

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
9 Downloads (Pure)


Recurrence is an ubiquitous feature which provides deep insights into the dynamics of real dynamical systems. A suitable tool for investigating recurrences is recurrence quantification analysis (RQA). It allows, e.g., the detection of regime transitions with respect to varying control parameters. We investigate the complexity of different coexisting nonlinear dynamical regimes of the plasma floating potential fluctuations at different magnetic fields and discharge voltages by using recurrence quantification variables, in particular, DET, L-max, and Entropy. The recurrence analysis reveals that the predictability of the system strongly depends on discharge voltage. Furthermore, the persistent behaviour of the plasma time series is characterized by the Detrended fluctuation analysis technique to explore the complexity in terms of long range correlation. The enhancement of the discharge voltage at constant magnetic field increases the nonlinear correlations; hence, the complexity of the system decreases, which corroborates the RQA analysis.

Original languageEnglish
Article number062312
Pages (from-to)1-10
Number of pages10
JournalPhysics of Plasmas
Issue number6
Early online date21 Jun 2016
Publication statusPublished - Jun 2016

Bibliographical note

The authors are thankful to BRNS-DAE, Government of India for the financial support under the project grant (Reference No. 2013/34/29/BRNS). The authors would like to express their heartfelt thanks to all the members of plasma Physics division of Saha Institute of Nuclear Physics for their help and constant support.


Dive into the research topics of 'Investigation of complexity dynamics in a DC glow discharge magnetized plasma using recurrence quantification analysis'. Together they form a unique fingerprint.

Cite this