A hybrid (Monte Carlo/deterministic) approach for multi-dimensional radiation transport

A novel hybrid Monte Carlo transport scheme is demonstrated in a scene with solar illumination, scattering and absorbing 2D atmosphere, a textured reflecting mountain, and a small detector located in the sky (mounted on a satellite or a airplane). It uses a deterministic approximation of an adjoint transport solution to reduce variance, computed quickly by ignoring atmospheric interactions. This allows significant variance and computational cost reductions when the atmospheric scattering and absorption coefficient are small. When combined with an atmospheric photon-redirection scheme, significant variance reduction (equivalently acceleration) is achieved in the presence of atmospheric interactions.

► We introduce a variance reduction scheme for Monte Carlo (MC) transport.
► The primary application is atmospheric remote sensing.
► The technique first solves the adjoint problem using a deterministic solver.
► Next, the adjoint solution is used as an importance function for the MC solver.
► The adjoint problem is solved quickly since it ignores the volume.