  We propose an efficient, robust, Lagrangian (characteristic-based) transport
solver for the time-dependent thermal radiative Transfer (TRT) applications
within the context of a moment-accelerated (High-Order/Low-Order, HOLO)
algorithm. This novel transport algorithm inherits the best features of both
particle methods (e.g., time accuracy, phase-space adaptivity, positivity) and
deterministic, grid-based methods (e.g., no stochastic noise). Particles are
evolved by the method of characteristics, with a time-dependent weight that
accounts for stiff absorption and reemission process self-consistently. As a
result, this approach is able to obtain accurate results while employing large
time steps and a moderate number of particles (compared to Implicit Monte
Carlo).
