8,595 research outputs found

    A constant-time algorithm for middle levels Gray codes

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    For any integer nβ‰₯1n\geq 1 a middle levels Gray code is a cyclic listing of all nn-element and (n+1)(n+1)-element subsets of {1,2,…,2n+1}\{1,2,\ldots,2n+1\} such that any two consecutive subsets differ in adding or removing a single element. The question whether such a Gray code exists for any nβ‰₯1n\geq 1 has been the subject of intensive research during the last 30 years, and has been answered affirmatively only recently [T. M\"utze. Proof of the middle levels conjecture. Proc. London Math. Soc., 112(4):677--713, 2016]. In a follow-up paper [T. M\"utze and J. Nummenpalo. An efficient algorithm for computing a middle levels Gray code. To appear in ACM Transactions on Algorithms, 2018] this existence proof was turned into an algorithm that computes each new set in the Gray code in time O(n)\mathcal{O}(n) on average. In this work we present an algorithm for computing a middle levels Gray code in optimal time and space: each new set is generated in time O(1)\mathcal{O}(1) on average, and the required space is O(n)\mathcal{O}(n)

    Problems on q-Analogs in Coding Theory

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    The interest in qq-analogs of codes and designs has been increased in the last few years as a consequence of their new application in error-correction for random network coding. There are many interesting theoretical, algebraic, and combinatorial coding problems concerning these q-analogs which remained unsolved. The first goal of this paper is to make a short summary of the large amount of research which was done in the area mainly in the last few years and to provide most of the relevant references. The second goal of this paper is to present one hundred open questions and problems for future research, whose solution will advance the knowledge in this area. The third goal of this paper is to present and start some directions in solving some of these problems.Comment: arXiv admin note: text overlap with arXiv:0805.3528 by other author

    New constructions for covering designs

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    A (v,k,t)(v,k,t) {\em covering design}, or {\em covering}, is a family of kk-subsets, called blocks, chosen from a vv-set, such that each tt-subset is contained in at least one of the blocks. The number of blocks is the covering's {\em size}, and the minimum size of such a covering is denoted by C(v,k,t)C(v,k,t). This paper gives three new methods for constructing good coverings: a greedy algorithm similar to Conway and Sloane's algorithm for lexicographic codes~\cite{lex}, and two methods that synthesize new coverings from preexisting ones. Using these new methods, together with results in the literature, we build tables of upper bounds on C(v,k,t)C(v,k,t) for v≀32v \leq 32, k≀16k \leq 16, and t≀8t \leq 8.

    Constructions of Snake-in-the-Box Codes for Rank Modulation

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    Snake-in-the-box code is a Gray code which is capable of detecting a single error. Gray codes are important in the context of the rank modulation scheme which was suggested recently for representing information in flash memories. For a Gray code in this scheme the codewords are permutations, two consecutive codewords are obtained by using the "push-to-the-top" operation, and the distance measure is defined on permutations. In this paper the Kendall's Ο„\tau-metric is used as the distance measure. We present a general method for constructing such Gray codes. We apply the method recursively to obtain a snake of length M2n+1=((2n+1)(2n)βˆ’1)M2nβˆ’1M_{2n+1}=((2n+1)(2n)-1)M_{2n-1} for permutations of S2n+1S_{2n+1}, from a snake of length M2nβˆ’1M_{2n-1} for permutations of~S2nβˆ’1S_{2n-1}. Thus, we have lim⁑nβ†’βˆžM2n+1S2n+1β‰ˆ0.4338\lim\limits_{n\to \infty} \frac{M_{2n+1}}{S_{2n+1}}\approx 0.4338, improving on the previous known ratio of lim⁑nβ†’βˆž1Ο€n\lim\limits_{n\to \infty} \frac{1}{\sqrt{\pi n}}. By using the general method we also present a direct construction. This direct construction is based on necklaces and it might yield snakes of length (2n+1)!2βˆ’2n+1\frac{(2n+1)!}{2} -2n+1 for permutations of S2n+1S_{2n+1}. The direct construction was applied successfully for S7S_7 and S9S_9, and hence lim⁑nβ†’βˆžM2n+1S2n+1β‰ˆ0.4743\lim\limits_{n\to \infty} \frac{M_{2n+1}}{S_{2n+1}}\approx 0.4743.Comment: IEEE Transactions on Information Theor
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