A Central Limit Theorem for the Length of the Longest Common Subsequences in Random Words

Abstract: Let $(X_i){i \geq 1}$ and $(Y_i){i\geq1}$ be two independent sequences of independent identically distributed random variables taking their values in a common finite alphabet and having the same law. Let $LC_n$ be the length of the longest common subsequences of the two random words $X_1\cdots X_n$ and $Y_1\cdots Y_n$. Under a lower bound assumption on the order of its variance, $LC_n$ is shown to satisfy a central limit theorem. This is in contrast to the limiting distribution of the length of the longest common subsequences in two independent uniform random permutations of ${1, \dots, n}$, which is shown to be the Tracy-Widom distribution.