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Simulations of multiscale solutions to differential equations often require a reduction in the number of unknowns compared to those in a standard discretization. This is in order to limit the memory requirement and the computational complexity. We will discuss common reduction techniques based on mesh refinements in the light of classical and novel sampling theorems from information theory.