LSP Code

The LSP code, a software product of Voss Scientific Corporation, is an advanced 3D electromagnetic particle-in-cell (PIC) code designed for complex, large-scale plasma simulations on parallel and serial platforms; the numerical code supports Cartesian, cylindrical, and spherical coordinate systems and can also be used in 1D and 2D geometries. Various explicit and implicit algorithms are implemented in the code for solving the field equations and equations of motion. Additional complex and sophisticated algorithms implemented in the LSP code include but are not limited to: a hybrid kinetic - fluid electron model; field emission models from object boundaries (stimulated by particle bombardment, field-stresses, Child-Langmuir emission, etc.); auxiliary circuit models; transmission-line boundaries; inclusion of arbitrary electric and magnetic susceptibilities, dispersive magnetic materials; external (applied) electric and magnetic field models, secondary particle generation at material surfaces; backscattering; multiple scattering events and energy loss; surface heating and energy deposition; thermal and/or stimulated desorption of neutrals and ions from surfaces; ionization of neutrals, ion stripping, photoionization, and interparticle collisions.

The Large-Scale Plasma (LSP) Particle-In-Cell (PIC) code is a commercial code that is actively being used for many applications. It has several attractive features: it comes with source code so it can be scrutinized and even modified and recompiled, and it is relatively easy to learn to use. However, for low-temperature plasma applications we encountered several issues that we have now resolved. We refer to this improved version of the code as PPPL-LSP. PPPL-LSP allows us to perform large two-dimensional and small three-dimensional simulations of low-temperature plasma, see Fig. 2. The major code improvement of PPPL-LSP is the addition of a direct electrostatic (ES) field solver. To enable simulations of plasma devices with a prescribed current flowing through them, an algorithm for a new external-circuit model was developed and implemented. A new rejection-method algorithm for SEE was implemented. A set of Python scripts were also developed to complement the existing P4 post processor for plotting and analyzing simulation data