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Predicting observational signatures of coronal heating by Alfv?n waves and nanoflares  

Patrick Antolin   Submitted: 2008-12-13 01:58

Alfv?n waves can dissipate their energy by means of nonlinear mechanisms, and constitute good candidates to heat and maintain the solar corona to the observed few million degrees. Another appealing candidate is nanoflare reconnection heating, in which energy is released through many small magnetic reconnection events. Distinguishing the observational features of each mechanism is an extremely difficult task. On the other hand, observations have shown that energy release processes in the corona follow a power-law distribution in frequency whose index may tell us whether small heating events contribute substantially to the heating or not. In this work we show a link between the power-law index and the operating heating mechanism in a loop. We set up two coronal loop models: in the first model Alfv?n waves created by footpoint shuffling nonlinearly convert to longitudinal modes which dissipate their energy through shocks; in the second model numerous heating events with nanoflare-like energies are input randomly along the loop, either distributed uniformly or concentrated at the footpoints. Both models are based on a 1.5-dimensional MHD code. The obtained coronae differ in many aspects; for instance, in the flow patterns along the loop and the simulated intensity profile that Hinode XRT would observe. The intensity histograms display power-law distributions whose indexes differ considerably. This number is found to be related to the distribution of the shocks along the loop. We thus test the observational signatures of the power-law index as a diagnostic tool for the above heating mechanisms and the influence of the location of nanoflares.

Authors: P. Antolin, K. Shibata, T. Kudoh, D. Shiota, D. Brooks
Projects: None

Publication Status: Published in ApJ 688, 669-682
Last Modified: 2008-12-14 17:43
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Predicting observational signatures of coronal heating by Alfv?n waves and nanoflares

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