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Explicit construction of RIP matrices is Ramsey-hard (1805.11238v2)

Published 29 May 2018 in math.PR, cs.IT, math.IT, and stat.CO

Abstract: Matrices $\Phi\in\R{n\times p}$ satisfying the Restricted Isometry Property (RIP) are an important ingredient of the compressive sensing methods. While it is known that random matrices satisfy the RIP with high probability even for $n=\log{O(1)}p$, the explicit construction of such matrices defied the repeated efforts, and the most known approaches hit the so-called $\sqrt{n}$ sparsity bottleneck. The notable exception is the work by Bourgain et al \cite{bourgain2011explicit} constructing an $n\times p$ RIP matrix with sparsity $s=\Theta(n{{1\over 2}+\epsilon})$, but in the regime $n=\Omega(p{1-\delta})$. In this short note we resolve this open question in a sense by showing that an explicit construction of a matrix satisfying the RIP in the regime $n=O(\log2 p)$ and $s=\Theta(n{1\over 2})$ implies an explicit construction of a three-colored Ramsey graph on $p$ nodes with clique sizes bounded by $O(\log2 p)$ -- a question in the extremal combinatorics which has been open for decades.

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