Sparse grid techniques for particle-in-cell schemes
arXiv:1607.06516 · doi:10.1088/1361-6587/59/2/024002
Abstract
We propose the use of sparse grids to accelerate particle-in-cell (PIC) schemes. By using the so-called `combination technique' from the sparse grids literature, we are able to dramatically increase the size of the spatial cells in multi-dimensional PIC schemes while paying only a slight penalty in grid-based error. The resulting increase in cell size allows us to reduce the statistical noise in the simulation without increasing total particle number. We present initial proof-of-principle results from test cases in two and three dimensions that demonstrate the new scheme's efficiency, both in terms of computation time and memory usage.
References in corpus (7)
- Ab-initio pulsar magnetosphere: three-dimensional particle-in-cell simulations of axisymmetric pulsars
- Exploiting multi-scale parallelism for large scale numerical modelling of laser wakefield accelerators
- Ion acceleration from laser-driven electrostatic shocks
- A multi-dimensional, energy- and charge-conserving, nonlinearly implicit, electromagnetic Vlasov-Darwin particle-in-cell algorithm
- Collisionless Reconnection in the Large Guide Field Regime: Gyrokinetic Versus Particle-in-Cell Simulations
- Modern Gyrokinetic Particle-In-Cell Simulation of Fusion Plasmas on Top Supercomputers
- A sparse grid discontinuous Galerkin method for high-dimensional transport equations and its application to kinetic simulations
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