The average-case complexity of the Word Problem for groups of matrices over~$\mathbb{Q}$ is linear
We show that the Word Problem in finitely generated subgroups of $\textsf{GL}_d(\mathbb{Q})$ can be solved in linear average-case complexity, both when the input words are chosen uniformly at random among the words of a given length and when they are chosen uniformly at random among the reduced words of a given length. This is done under the bit-complexity model, which accounts for the fact that large integers are handled (as numerators and denominators of rational numbers). Corollaries include the fact that the Word Problem can be solved in linear average-case complexity for finitely generated nilpotent or polycyclic groups. Our result also generalizes to matrices in $\textsf{GL}_d(R)$, where $R$ is an algebraic number field. And we show that no algorithm can solve this problem in sublinear worst-case or average-case complexity.