Problem reduction, renormalization, and memory

Details Problem reduction, renormalization, and memory Problem reduction, renormalization, and memory

2005-03-26

arxiv.org/abs/math/0503612v1

Mathematics

Numerical Analysis

Scientific paper

Methods for the reduction of the complexity of computational problems are presented, as well as their connections to renormalization, scaling, and irreversible statistical mechanics. Several statistically stationary cases are analyzed; for time dependent problems averaging usually fails, and averaged equations must be augmented by appropriate memory and random forcing terms. Approximations are described and examples are given.

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