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Beating Fredman-Koml\'{o}s for perfect $k$-hashing

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arxiv 1805.04151 v1 pith:OYSU7AMP submitted 2018-05-10 cs.IT cs.DMcs.DSmath.COmath.IT

classification cs.ITcs.DMcs.DSmath.COmath.IT
keywords boundhashcodeeveryboundscertaincodewordsdots
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abstract

We say a subset $C \subseteq \{1,2,\dots,k\}^n$ is a $k$-hash code (also called $k$-separated) if for every subset of $k$ codewords from $C$, there exists a coordinate where all these codewords have distinct values. Understanding the largest possible rate (in bits), defined as $(\log_2 |C|)/n$, of a $k$-hash code is a classical problem. It arises in two equivalent contexts: (i) the smallest size possible for a perfect hash family that maps a universe of $N$ elements into $\{1,2,\dots,k\}$, and (ii) the zero-error capacity for decoding with lists of size less than $k$ for a certain combinatorial channel. A general upper bound of $k!/k^{k-1}$ on the rate of a $k$-hash code (in the limit of large $n$) was obtained by Fredman and Koml\'{o}s in 1984 for any $k \geq 4$. While better bounds have been obtained for $k=4$, their original bound has remained the best known for each $k \ge 5$. In this work, we obtain the first improvement to the Fredman-Koml\'{o}s bound for every $k \ge 5$. While we get explicit (numerical) bounds for $k=5,6$, for larger $k$ we only show that the FK bound can be improved by a positive, but unspecified, amount. Under a conjecture on the optimum value of a certain polynomial optimization problem over the simplex, our methods allow an effective bound to be computed for every $k$.

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  1. Quantum Overlapping Tomography

    quant-ph 2019-08 conditional novelty 7.0 of 10

    All k-qubit reduced density matrices of an n-qubit state can be reconstructed from e^{O(k)} log^2(n) rounds of parallel product measurements using perfect hash families.

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