Statistical Properties of Synthetic Nanoflares

Statistical properties of flares are a powerful tool for addressing the upper solar atmosphere heating problem.We simulate time series of synthetic flares by means of a dynamic model of the atmospheric magnetic field in which magnetic loop footpoints are controlled by photospheric flows computed through a n-body algorithm. The n-body simulation reproduces the behavior of a system where large spatial organization scales (i.e., mesogranulation) occur from the interaction of small-scale advection flows (i.e., granulation). The frequency function of the emitted magnetic energies obtained from the simulation is well approximated by a power law with index 2:4, while the frequency function of the waiting times between emissions shows a Poisson-like behavior with a deviation for longer times. The flare model yields a fairly intuitive interpretation ofmagnetic reconnection processes as magnetic field reconfigurations triggered by passive advection of magnetic footpoints through photospheric space-temporal correlated flows