Solar Flare Electron Acceleration: progress and challenges

James Drake, University of Maryland

Magnetic reconnection is a significant driver of energetic particles in flares both on the sun and beyond. Simple estimates reveal that reconnection electric fields in solar flares greatly exceed the Dreiser runaway field so collisions are not expected to play a significant role in energetic electron production. Single x-line models fail to explain the large number of energetic electrons seen in flares. However, simulations reveal that reconnection becomes turbulent in the flare environment, consistent with observations of non-thermal broadening of spectral lines. Magnetic energy release and particle acceleration therefore take place in a multi-x-line environment. There are three basic mechanisms for particle energy gain in such a system: motion along parallel electric fields; and the magnetic curvature and gradient B drifts along perpendicular fields. The latter two produce the classical Fermi and betatron acceleration, respectively. Simulations reveal that electron heating and acceleration are dominated by parallel electric fields and Fermi reflection with Fermi dominating in reconnection with modest guide fields and parallel electric fields dominating with strong guide fields. A major surprise is that in the strong guide field limit where parallel electric fields dominate electron energy gain, the production of the most energetic electrons drops precipitously. Parallel electric fields are therefore inefficient drivers of very energetic electrons. The rate of production of energetic electrons dramatically increases in turbulent reconnecting systems (in 3D). Major challenges are to understand how relativistic electrons are "confined" as they gain significant energy and what mechanisms lead to and control the powerlaw energy spectra that characterize energetic electrons in flares. Finally, the enormous separation between kinetic and macroscales means that modeling particle acceleration during energy release in flares is a major computational challenge.