Evidence of nonlinearity in presence of external forcing and magnetic field in a glow discharge plasma

Saha, Debajyoti; Shaw, Pankaj Kumar; Ghosh, Samir; Janaki, M. S.; Iyengar, A. N. Sekar

doi:10.1016/j.chaos.2017.03.005

Cited by 5 publications

(2 citation statements)

References 37 publications

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“…The mean of D(r, m) for all r values is calculated to yield D(m) for every m = 1, 2, … , L while L ≤ 10 . For a stochastic time series D(m) exhibits a monotonically increasing trend towards infinity with m. However, if the process is deterministic, this continuous increment of D(m) ceases at some small m where it saturates in a plateau [45]. This saturated value of D(m) gives the correlation dimension.…”

Section: Correlation Dimension Analysismentioning

confidence: 99%

Analysis of fractality and complexity of the planetary K-index

Chattopadhyay¹,

Chandra

Khondekar³

et al. 2021

SN Appl. Sci.

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The objective of this research is to explore the inherent complexities and multifractal properties of the underlying distributions in the daily Planetary K-index time series collected from NOAA Space Weather Prediction Center. In this article, non-stationary and nonlinear characteristics of the signal have been explored using Smoothed Pseudo Wigner–Ville Distribution and Delay Vector Variance algorithms, respectively, while Recurrence Plot, 0–1 test, Recurrence Quantification Analysis and correlation dimension analysis have been applied to confirm and measure the chaos in the signal under consideration. Multifractal detrending moving average has been used to evaluate the multifractality and also recognise the singularities of the signal. The result of these analyses validates the nonstationary and nonlinear characteristics of the Planetary K-index signal, while a significant presence of deterministic chaos in it has also been noticed. It has also been confirmed that the Planetary K-index exhibits multifractal nature with positive persistence. The long-range temporal association and also the large pdf are discovered to be the primary factors that contribute to the multifractal behaviour of the Kp-index.

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Section: Correlation Dimension Analysismentioning

confidence: 99%

Analysis of fractality and complexity of the planetary K-index

Chattopadhyay¹,

Chandra

Khondekar³

et al. 2021

SN Appl. Sci.

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“…Presence of strong trends associated with nonstationarity can lead to the false detection of scaling exponent. So for the reliable detection of power law exponent (α) it is essential to distinguish trends [21] from the long range fluctuation [22,23] intrinsic in the data. Most economic and financial time [24,25,26]series are persistent with α >0.5.…”

Section: Introductionmentioning

confidence: 99%

Quantification of scaling exponent with Crossover type phenomena for different types of forcing in DC glow discharge plasma

Saha

Shaw

Ghosh

et al. 2018

Physica A: Statistical Mechanics and its Applications

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We have carried out a detailed study of scaling region using detrended fractal analysis test by applying different forcing likewise noise, sinusoidal, square on the floating potential fluctuations acquired under different pressures in a DC glow discharge plasma. The transition in the dynamics is observed through recurrence plot techniques which is an efficient method to observe the critical regime transitions in dynamics. The complexity of the nonlinear fluctuation has been revealed with the help of recurrence quantification analysis which is a suitable tool for investigating recurrence, an ubiquitous feature providing a deep insight into the dynamics of real dynamical system. An informal test for stationarity which checks for the compatibility of nonlinear approximations to the dynamics made in different segments in a time series has been proposed. In case of sinusoidal, noise, square forcing applied on fluctuation acquired at P=0.12mbar only one dominant scaling region is observed whereas the forcing applied on fluctuation (P=0.004mbar) two prominent scaling regions have been explored reliably using different forcing amplitudes indicating the signature of crossover phenomena. Furthermore a persistence long range behaviour has been observed in one of these scaling regions. A comprehensive study of the quantification of scaling exponents has been carried out with the increase in amplitude and frequency of sinusoidal, square type of forcings. The scalings exponent is envisaged to be the roughness of the time series. The method provides a single quantitative idea of the scaling exponent to quantify the correlation properties of a signal.

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