  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.
