Abstract
We model radiation transport by advancing computational photons through phase space with solutions to a set of stochastic differential equations of motion. Random numbers that appear in the equations of motion are sampled with deterministically chosen Gaussian quadrature weights and abscissas. In this way, the advantages of particle Monte Carlo are realized without generating statistical noise. We demonstrate this technique by performing one- and two-dimensional test problems in which gray radiation is energetically coupled to stationary material. Scattering is accomplished with a Fokker–Planck scattering operator. Free streaming, diffusion and Marshak waves are recovered in appropriate limits.
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