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A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential-transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized ai*e albedo scattering, Monte Carlo coupling techniques with discrete ordinatesdoi:10.13182/nse86-a18177 fatcat:zwymx3246jcold2fyoaebumtcm