Improved Lower Bounds on the Expected Length of Longest Common Subsequences

July 15, 2024 Β· Declared Dead Β· πŸ› International Symposium on Information Theory

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Authors George T. Heineman, Chase Miller, Daniel Reichman, Andrew Salls, GΓ‘bor SΓ‘rkΓΆzy, Duncan Soiffer arXiv ID 2407.10925 Category cs.DS: Data Structures & Algorithms Citations 2 Venue International Symposium on Information Theory Last Checked 4 months ago
Abstract
It has been proven that, when normalized by $n$, the expected length of a longest common subsequence of $d$ random strings of length $n$ over an alphabet of size $Οƒ$ converges to some constant that depends only on $d$ and $Οƒ$. These values are known as the ChvΓ‘tal-Sankoff constants, and determining their exact values is a well-known open problem. Upper and lower bounds are known for some combinations of $Οƒ$ and $d$, with the best lower and upper bounds for the most studied case, $Οƒ=2, d=2$, at $0.788071$ and $0.826280$, respectively. Building off previous algorithms for lower-bounding the constants, we implement runtime optimizations, parallelization, and an efficient memory reading and writing scheme to obtain an improved lower bound of $0.792665992$ for $Οƒ=2, d=2$. We additionally improve upon almost all previously reported lower bounds for the ChvΓ‘tal-Sankoff constants when either the size of alphabet, the number of strings, or both are larger than 2.
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