Bit Complexity of Jordan Normal Form and Spectral Factorization

Abstract: We study the bit complexity of two related fundamental computational problems in linear algebra and control theory. Our results are: (1) An $$\tilde{O}(n<sup>{\omega+3}a+n<sup>4a<sup>2+n<sup>\omega\log(1/\epsilon))$$ time algorithm for finding an $\epsilon-$approximation to the Jordan Normal form of an integer matrix with $a-$bit entries, where $\omega$ is the exponent of matrix multiplication. (2) An $$\tilde{O}(n<sup>6d<sup>6a+n<sup>4d<sup>4a<sup>2+n<sup>3d<sup>3\log(1/\epsilon))$$ time algorithm for $\epsilon$-approximately computing the spectral factorization $P(x)=Q<sup>*(x)Q(x)$ of a given monic $n\times n$ rational matrix polynomial of degree $2d$ with rational $a-$bit coefficients having $a-$bit common denominators, which satisfies $P(x)\succeq 0$ for all real $x$. The first algorithm is used as a subroutine in the second one. Despite its being of central importance, polynomial complexity bounds were not previously known for spectral factorization, and for Jordan form the best previous best running time was an unspecified polynomial in $n$ of degree at least twelve \cite{cai1994computing}. Our algorithms are simple and judiciously combine techniques from numerical and symbolic computation, yielding significant advantages over either approach by itself.