Recurrence quantification analysis of turbulent fluctuations in the plasma edge of Tokamak Chauffage Alfvén Brésilien tokamak

Abstract

A generalized flux function for three-dimensional magnetic reconnection Phys. Plasmas 18, 102118 (2011) Time-frequency analysis for microwave reflectometry data processing in the HL-2A tokamak Rev. Sci. Instrum. 82, 103508 (2011) Recurrences are close returns of a given state in a time series, and can be used to identify different dynamical regimes and other related phenomena, being particularly suited for analyzing experimental data. In this work, we use recurrence quantification analysis to investigate dynamical patterns in scalar data series obtained from measurements of floating potential and ion saturation current at the plasma edge of the Tokamak Chauffage Alfvén Brésilien ͓R. M. O. Galvão et al., Plasma Phys. Controlled Fusion 43, 1181 ͑2001͔͒. We consider plasma discharges with and without the application of radial electric bias, and also with two different regimes of current ramp. Our results indicate that biasing improves confinement through destroying highly recurrent regions within the plasma column that enhance particle and heat transport.

Analysis of the influence of external biasing on Texas Helimak turbulence

“…29 The obtained RPs are homogeneous, as expected for the analyzed stationary series. The turbulence differences can be identified in the three RPs of Figure 7 by their characteristic patterns, or structures, made of certain distributions of pixels.…”

“…As observed in Torpex, 31 K and S values are approximately distributed along a parabola. This deviation from a Gaussian is due to the presence of intermittent bursts, a phenomenon common to several magnetic confinement devices, 29,33 and the parabolic relationship between K and S has been observed in several kinds of plasma turbulence. 34 Next, for data from probes at R ¼ 1.170 m and a shot with bias ¼ þ15 V, we present in Fig.…”

“…While the RPs depend on the values of the embedding dimension d and the threshold e, the relative trend is quite stable with respect to these parameters. 27,29 Recurrence quantification analysis consists of a series of measures obtained from a recurrence plot which can elucidate various aspects of the system behavior. For example, stationary time series give recurrence plots which are homogeneous, while for non stationary ones the recurrences are mainly concentrated close to the main diagonal.…”

“…A systematic way to investigate the occurrence of recurrences in a time series is by means of recurrence plots (RPs), which are two-dimensional graphical representations of the matrix whose elements are R i,j ¼ H(e À ||X i À X j ||), i, j ¼ 1, 2,… N, where e is a predetermined threshold, H is the Heaviside unit step, ||…|| is the Euclidean (or another suitable) norm. [27][28][29] The recurrence plot is obtained by assigning a black (white) pixel to the points for which R i,j ¼ 1(0). While the RPs depend on the values of the embedding dimension d and the threshold e, the relative trend is quite stable with respect to these parameters.…”

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

“…8 In fusion plasmas, turbulence and associated cross field transport have been investigated by using RQA. 9,10 It has also been utilized as an emerging tool to analyze simulation data of ion temperature gradient turbulence 11 and dissipative trapped electron mode turbulence, 12 and to characterize transport dynamics. Recently, we have used RQA to study order-chaos transition in an unmagnetized DC glow discharge plasma oscillation.…”