  A matrix $\Phi \in \mathbb{R}^{Q \times N}$ satisfies the restricted isometry
property if $\|\Phi x\|_2^2$ is approximately equal to $\|x\|_2^2$ for all
$k$-sparse vectors $x$. We give a construction of RIP matrices with the optimal
$Q = O(k \log(N/k))$ rows using $O(k\log(N/k)\log(k))$ bits of randomness. The
main technical ingredient is an extension of the Hanson-Wright inequality to
$\epsilon$-biased distributions.
