A multiscale, time reversible method for computing the effective slow
behavior of systems of highly oscillatory ordinary differential equations is
presented. The proposed method relies on correctly tracking a set of slow
variables that is sufficient to approximate any variable and functional that
are slow under the dynamics of the system. The algorithm follows the
framework of the heterogeneous multiscale method. The notion of time
reversibility in the multiple time-scale setting is discussed. The algorithm
requires nontrivial matching between the microscopic state variables and the
macroscopic slow ones. Numerical examples show the efficiency of the
multiscale method and the advantages of time reversibility.