A Vlasov-Hybrid Code with Hermite Expansion of the Distribution Function for the Study of Low Growth Rate Instabilities
Abstract
Within turbulence there are many phenomena which are currently unsolved. In
the solar wind temperature anisotropies and low growth rates instability have a
dominant role in de ning the turbulent behaviour of plasma. Due to the non linearity
of the equations involved in the description of the physics of plasmas numerical
simulations are a fundamental tool to study the dynamics of turbulent phenomena.
In particular, hybrid codes are widely used in space plasma applications due to their
ability to simulate large regions of volume maintaining some kinetic e ects.
However, due to the sensitivity to the initial level of noise in the simulation, low
growth rate instabilities are particularly di cult to simulate. Particle in Cell-hybrid
simulations require too many particles to reduce the initial noise, while Vlasovhybrid
simulations require too many grid points to fully discretize spatial and velocity
phase spaces.
We present here a Vlasov-hybrid algorithm and code implementation where the
distribution function is expanded in series of Hermite functions. Thanks to the
properties of these it is possible to project the Vlasov equation to nd an equation
for each coe cient of the expansion. These coe cients are advanced in time using a
Current Advance Method algorithm with splitting method for the Vlasov operator.
The former is treated explicitly, while the latter is treated implicitly with a GMRES
solver. The current is advanced with a temporal ODE derived taking moments
of the Vlasov equation. A 1D3V code is implemented, tested and used to study
low growth rate instabilities such as a proton cyclotron instability and a ion/ion
right hand resonant instability with small relative velocity drift between beam and
core populations. The results are compared with existing hybrid algorithms that we
implemented. A 2D3V parallelized version of the code is implemented and described
here. Initial results are presented and future improvements are discussed.
Authors
Boffa, FrancescoCollections
- Theses [3651]