A new wavelet-based paradigm for hierarchical coarse-graining applied to materials modeling

We outline how the wavelet transform, a hierarchical averaging scheme, can be used to perform both structural and topological coarse-graining in systems with multiscale physical behavior, such as Ising lattices and polymer models. We illustrate how to create sampling mechanisms, which we call wavelet-accelerated Monte Carlo (WAMC), to study these systems and obtain qualitative and quantitatively accurate results in orders of magnitude less time than using atomistic simulations.