Embedding minimal dynamical systems into Hilbert cubes

Abstract: We study the problem of embedding minimal dynamical systems into the shift action on the Hilbert cube $\left([0,1]^N\right)^{\mathbb{Z}}$. This problem is intimately related to the theory of mean dimension, which counts the averaged number of parameters of dynamical systems. Lindenstrauss proved that minimal systems of mean dimension less than $N/36$ can be embedded into $\left([0,1]^N\right)^{\mathbb{Z}}$, and he proposed the problem of finding the optimal value of the mean dimension for the embedding. We solve this problem by proving that minimal systems of mean dimension less than $N/2$ can be embedded into $\left([0,1]^N\right)^{\mathbb{Z}}$. The value $N/2$ is optimal. The proof uses Fourier and complex analysis.