Conference paper or proceedings

Correlation and scaling properties of non-stationary intensity fluctuations in coronal EUVtime series in different physical environments

Previously we have used EUV observations from AIA/SDO to examine properties of energy deposition into coronal-loops in non-flaring active region (AR) cores. The evolution of the loop apex intensity, temperature, and electron density indicate that the loops are impulsively heated in a mode compatible with high intensity nanoflare storms characterized by a progressive cooling pattern in the EUV lines with the hot channels leading the emission. Spectra of the hot 131 Å intensity (basically Fe XXI) and of the energy dissipation in a 2D model of loop magneto-turbulence compatible with nanoflare statistics, both exhibit three scaling regimes with low frequencies corresponding to 1/f noise, the intermediate range indicating a persistent process, and high frequencies corresponding to white noise. The varying power law behavior in these spectra indicates that both the observational and the simulated time series are not stationary. Therefore to extend the analysis beyond the AR loops we apply the method of detrended fluctuation analysis (DFA) that was developed to study the long-range correlations in non-stationary signals. DFA provides a scaling exponent that characterizes the correlation properties of the signal and which can be related both to the spectral exponents and to the Hurst exponent. In areas of diffuse emission and for all the spectral channels the time series of intensity fluctuations are characterized by scaling exponents that indicate a weak positive correlation across all time scales. In regions with intermittent intensity brightenings a cross-over occurs at timescales near 10 - 20 min with different exponents describing the degree of positive correlation of the intensity fluctuations at short and long time scales. Qualitative differences exist between the exponents of the hotter and the cooler channels. We have further compared the scaling properties of the time series associated with different physical environments distinguished by the possibility of underlying nanoflare storms, or by the strength of the magnetic field in contemporaneous HMI images. Another comparison is made to the scaling properties of simulations of energy dissipation in magnetoturbulence.