English

Bit Complexity of Jordan Normal Form and Spectral Factorization

Data Structures and Algorithms 2022-11-29 v2 Numerical Analysis Symbolic Computation Numerical Analysis Optimization and Control

Abstract

We study the bit complexity of two related fundamental computational problems in linear algebra and control theory. Our results are: (1) An O~(nω+3a+n4a2+nωlog(1/ϵ))\tilde{O}(n^{\omega+3}a+n^4a^2+n^\omega\log(1/\epsilon)) time algorithm for finding an ϵ\epsilon-approximation to the Jordan Normal form of an integer matrix with aa-bit entries, where ω\omega is the exponent of matrix multiplication. (2) An O~(n6d6a+n4d4a2+n3d3log(1/ϵ))\tilde{O}(n^6d^6a+n^4d^4a^2+n^3d^3\log(1/\epsilon)) time algorithm for ϵ\epsilon-approximately computing the spectral factorization P(x)=Q(x)Q(x)P(x)=Q^*(x)Q(x) of a given monic n×nn\times n rational matrix polynomial of degree 2d2d with rational aa-bit coefficients having aa-bit common denominators, which satisfies P(x)0P(x)\succeq 0 for all real xx. 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 nn 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.

Keywords

Cite

@article{arxiv.2109.13956,
  title  = {Bit Complexity of Jordan Normal Form and Spectral Factorization},
  author = {Papri Dey and Ravi Kannan and Nick Ryder and Nikhil Srivastava},
  journal= {arXiv preprint arXiv:2109.13956},
  year   = {2022}
}

Comments

19pp

R2 v1 2026-06-24T06:27:19.755Z