Approximately Hadamard matrices and Riesz bases in random frames

Abstract

An $n\times n$ matrix with $\pm 1$ entries which acts on ${\mathbb{R}}^n$ as a scaled isometry is called Hadamard. Such matrices exist in some, but not all dimensions. Combining number-theoretic and probabilistic tools we construct matrices with $\pm 1$ entries which act as approximate scaled isometries in ${\mathbb{R}}^n$ for all $n$. More precisely, the matrices we construct have condition numbers bounded by a constant independent of $n$. Using this construction, we establish a phase transition for the probability that a random frame contains a Riesz basis. Namely, we show that a random frame in ${\mathbb{R}}^n$ formed by $N$ vectors with independent identically distributed coordinates having a non-degenerate symmetric distribution contains many Riesz bases with high probability provided that $N\ge \exp (Cn)$. On the other hand, we prove that if the entries are subgaussian, then a random frame fails to contain a Riesz basis with probability close to $1$ whenever $N\le \exp (cn)$, where $c<C$ are constants depending on the distribution of the entries.