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[Solved]: Number of words of a given length in a regular language

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Problem Detail: 

Is there an algebraic characterization of the number of words of a given length in a regular language?

Wikipedia states a result somewhat imprecisely:

For any regular language $L$ there exist constants $\lambda_1,\,\ldots,\,\lambda_k$ and polynomials $p_1(x),\,\ldots,\,p_k(x)$ such that for every $n$ the number $s_L(n)$ of words of length $n$ in $L$ satisfies the equation $s_L(n)=p_1(n)\lambda_1^n+\dotsb+p_k(n)\lambda_k^n$.

It's not stated what space the $\lambda$'s live in ($\mathbb{C}$, I presume) and whether the function is required to have nonnegative integer values over all of $\mathbb{N}$. I would like a precise statement, and a sketch or reference for the proof.

Bonus question: is the converse true, i.e. given a function of this form, is there always a regular language whose number of words per length is equal to this function?

This question generalizes Question about the number of words in a regular language

Asked By : Gilles

Answered By : Yuval Filmus

Given a regular language $L$, consider some DFA accepting $L$, let $A$ be its transfer matrix ($A_{ij}$ is the number of edges leading from state $i$ to state $j$), let $x$ be the characteristic vector of the initial state, and let $y$ be the characteristic vector of the accepting states. Then $$ s_L(n) = x^T A^n y. $$

Jordan's theorem states that over the complex numbers, $A$ is similar to a matrix with blocks of one of the forms $$ \begin{pmatrix} \lambda \end{pmatrix}, \begin{pmatrix} \lambda & 1 \\ 0 & \lambda \end{pmatrix}, \begin{pmatrix} \lambda & 1 & 0 \\ 0 & \lambda & 1 \\ 0 & 0 & \lambda \end{pmatrix}, \begin{pmatrix} \lambda & 1 & 0 & 0 \\ 0 & \lambda & 1 & 0 \\ 0 & 0 & \lambda & 1 \\ 0 & 0 & 0 & \lambda \end{pmatrix}, \ldots $$ If $\lambda \neq 0$, then the $n$th powers of these blocks are $$ \begin{pmatrix} \lambda^n \end{pmatrix}, \begin{pmatrix} \lambda^n & n\lambda^{n-1} \\ 0 & \lambda^n \end{pmatrix}, \begin{pmatrix} \lambda^n & n\lambda^{n-1} & \binom{n}{2} \lambda^{n-2} \\ 0 & \lambda^n & n\lambda^{n-1} \\ 0 & 0 & \lambda^n \end{pmatrix}, \begin{pmatrix} \lambda^n & n\lambda^{n-1} & \binom{n}{2}\lambda^{n-2} & \binom{n}{3}\lambda^{n-3} \\ 0 & \lambda^n & n\lambda^{n-1} & \binom{n}{2}\lambda^{n-2} \\ 0 & 0 & \lambda^n & n\lambda^{n-1} \\ 0 & 0 & 0 & \lambda^n \end{pmatrix}, \ldots $$ Here's how we got to these formulas: write the block as $B = \lambda + N$. Successive powers of $N$ are successive secondary diagonals of the matrix. Using the binomial theorem (using the fact that $\lambda$ commutes with $N$), $$ B^n = (\lambda + n)^N = \lambda^n + n \lambda^{n-1} N + \binom{n}{2} \lambda^{n-2} N^2 + \cdots. $$ When $\lambda = 0$, the block is nilpotent, and we get the following matrices (the notation $[n = k]$ is $1$ if $n=k$ and $0$ otherwise): $$ \begin{pmatrix} [n=0] \end{pmatrix}, \begin{pmatrix} [n=0] & [n=1] \\ 0 & [n=0] \end{pmatrix}, \begin{pmatrix} [n=0] & [n=1] & [n=2] \\ 0 & [n=0] & [n=1] \\ 0 & 0 & [n=0] \end{pmatrix}, \begin{pmatrix} [n=0] & [n=1] & [n=2] & [n=3] \\ 0 & [n=0] & [n=1] & [n=2] \\ 0 & 0 & [n=0] & [n=1] \\ 0 & 0 & 0 & [n=0] \end{pmatrix} $$

Summarizing, every entry in $A^n$ is either of the form $\binom{n}{k} \lambda^{n-k}$ or of the form $[n=k]$, and we deduce that $$ s_L(n) = \sum_i p_i(n) \lambda_i^n + \sum_j c_j [n=j], $$ for some complex $\lambda_i,c_j$ and complex polynomials $p_i$. In particular, for large enough $n$, $$ s_L(n) = \sum_i p_i(n) \lambda_i^n. $$ This is the precise statement of the result.

We can go on and obtain asymptotic information about $s_L(n)$, but this is surprisingly non-trivial. If there is a unique $\lambda_i$ of largest magnitude, say $\lambda_1$, then $$ s_L(n) = p_1(n) \lambda_1^n (1 + o(1)). $$ Things get more complicated when there are several $\lambda$s of largest magnitude. It so happens that their angle must be rational (i.e. up to magnitude, they are roots of unity). If the LCM of the denominators is $d$, then the asymptotics of $s_L$ will very according to the remainder of $n$ modulo $d$. For some of these remainders, all $\lambda$s of largest magnitude cancel, and then the asymptotics "drops", and we have to iterate this procedure. The interested reader can check the details in Flajolet and Sedgewick's Analytic Combinatorics, Theorem V.3. They prove that for some $d$, integers $p_0,\ldots,p_{d-1}$ and reals $\lambda_0,\ldots,\lambda_{d-1}$, $$ s_L(n) = n^{p_{n\pmod{d}}} \lambda_{n\pmod{d}}^n (1 + o(1)). $$

Best Answer from StackOverflow

Question Source : http://cs.stackexchange.com/questions/1045

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