Investigating power law power spectra as a diagnostic of nanoflare coronal heating in active regions

Abstract:

Power spectra of time series of synthetic AIA emission derived from simulations of coronal heating in a realistic active region geometry are analyzed. The synthetic AIA emissions are the same as those described in Bradshaw & Viall 2016 ApJ, 821, 63. In those simulations, low, intermediate and high frequency nanoflare occurrence rates are postulated and the consequent synthetic AIA observations are calculated. Bradshaw & Viall (2016) calculate the time lags between hotter and cooler synthetic AIA channels derived via cross-correlation of time series, and show that these timelags are broadly similar to those derived from observational data. Power spectra of time series of synthetic AIA emission are fit by a model P(f) = Af^-n + C, where f is frequency, n>0, A>C>0. For all six synthetic AIA channels, it is shown that the fit power law index n depends on AIA channel, spatial location, and the frequency of nanoflare energy deposition. This suggests that power spectra of time series of observational AIA data contain information on the frequency of nanoflare energy deposition. We discuss the use of power law power spectra as a possible diagnostic of nanoflare heating in observational data. We demonstrated that the analysis of power spectra may provide further constraints on the distribution of heating frequencies in active regions, complementary to existing constraints derived from other observables such as emission measure slopes and time lags.