English

Generalized Wong sequences and their applications to Edmonds' problems

Computational Complexity 2014-06-27 v2 Data Structures and Algorithms

Abstract

We design two deterministic polynomial time algorithms for variants of a problem introduced by Edmonds in 1967: determine the rank of a matrix M whose entries are homogeneous linear polynomials over the integers. Given a linear subspace B of the n by n matrices over some field F, we consider the following problems: symbolic matrix rank (SMR) is the problem to determine the maximum rank among matrices in B, symbolic determinant identity testing (SDIT) is the question to decide whether there exists a nonsingular matrix in B. The constructive versions of these problems are asking to find a matrix of maximum rank, respectively a nonsingular matrix, if there exists one. Our first algorithm solves the constructive SMR when B is spanned by unknown rank one matrices, answering an open question of Gurvits. Our second algorithm solves the constructive SDIT when B is spanned by triangularizable matrices, but the triangularization is not given explicitly. Both algorithms work over finite fields of size at least n+1 and over the rational numbers, and the first algorithm actually solves (the non-constructive) SMR independently from the field size. Our main tool to obtain these results is to generalize Wong sequences, a classical method to deal with pairs of matrices, to the case of pairs of matrix spaces.

Keywords

Cite

@article{arxiv.1307.6429,
  title  = {Generalized Wong sequences and their applications to Edmonds' problems},
  author = {Gábor Ivanyos and Marek Karpinski and Youming Qiao and Miklos Santha},
  journal= {arXiv preprint arXiv:1307.6429},
  year   = {2014}
}

Comments

25 pages; improved presentation; fix some gaps

R2 v1 2026-06-22T00:57:05.916Z