Higher order sampling strategies in Monte-Carlo simulations of electron energy distribution functions in low temperature plasmas

Summary form only given. A strategy is presented which takes advantage of the higher order information (e.g., gradients) available on an energy interval to obtain high-resolution distribution functions. This strategy allows the use of coarse energy bins and a small number of particles, thereby significantly reducing the required computer time. The particles within an energy bin are sampled with the appropriate Legendre polynomial weighted value. With these weightings, it is possible to obtain higher-order derivatives from the summation of the weighted values on the interval by using the orthogonality property of the polynomials. The electron energy distribution functions that are generated can be easily parameterized to yield transport coefficients for use in fluid equations. This technique has particular relevance to determining transport coefficients for plasmas at low pressures near solid boundaries, where statistics in conventional Monte Carlo simulations are poor.