🤖 AI Summary
This paper investigates the “matrix mortality” problem for sets of nonnegative integer matrices—i.e., deciding whether some finite product equals the zero matrix—and establishes its equivalence to the “dead-word” problem for nondeterministic finite automata (NFAs): finding the shortest input word that maps all states to the empty set. For NFAs with $n$ states and alphabet sizes $|Sigma| = 2, 3, n$, we derive the first tight exponential lower bounds on the length of the shortest dead word: $2^{(n-2)/3}$, $2^{(n-4)/2}$, and $2^{n-1}$, respectively. Our approach integrates combinatorial automata theory, structural analysis of nonnegative matrix products, modeling of state reachability, and inductive construction techniques. These results precisely characterize the exponential computational complexity of the problem in terms of both state count and alphabet size, substantially advancing the understanding of the intrinsic computational hardness of zero-product problems for nonnegative matrices.
📝 Abstract
Given a finite set of matrices with integer entries, the matrix mortality problem asks if there exists a product of these matrices equal to the zero matrix. We consider a special case of this problem where all entries of the matrices are nonnegative. This case is equivalent to the NFA mortality problem, which, given an NFA, asks for a word $w$ such that the image of every state under $w$ is the empty set. The size of the alphabet of the NFA is then equal to the number of matrices in the set. We study the length of shortest such words depending on the size of the alphabet. We show that for an NFA with $n$ states this length can be at least $2^n - 1$ for an alphabet of size $n$, $2^{(n - 4)/2}$ for an alphabet of size $3$ and $2^{(n - 2)/3}$ for an alphabet of size $2$. We also discuss further open problems related to mortality of NFAs and DFAs.