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Matrices with Two Nonzero Entries per Row

Published: 24 June 2015 Publication History

Abstract

Matrices with two nonzero entries per row (or per column) occur in many contexts. For example, edge-vertex incidence matrices of graphs have this form. Also, the boundary matrix for the highest dimensional simplices in a simplicial complex sometimes has this form as well. In particular, the homology of a triangulation of a 2 dimensional non-self-intersecting surface is obtained from the Smith forms of 2 two-per-row matrices (the edge-vertex and triangle-edge boundary matrices).
For an n by n matrix having just two nonzero entries per row, we show that rank, determinant, LU decomposition, and linear system solution can all be done in O(n) arithmetic operations (algebraic complexity). In the LU decomposition, U is bidiagonal and L, generally dense, is represented as a blackbox occupying O(n) space and such that matrix vector product with L and with its inverse can both be performed in O(n) arithmetic operations.
If the nonzero entries are restricted to one and minus one then rank, LU decomposition, and Smith normal form can be computed in essentially O(n) bit operations (ignoring log factors). In this limited situation, Smith form is meaningfully defined over any ring. Determinant and linear system solution can each be performed with O(n) additions and negations in the entry ring.
For integer two-per-row matrices with the nonzeros not limited to one and minus one, the methods here can be combined with standard techniques for algorithms of bit complexity greater than O(n) but less than the complexity for general matrices.

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cover image ACM Conferences
ISSAC '15: Proceedings of the 2015 ACM International Symposium on Symbolic and Algebraic Computation
June 2015
374 pages
ISBN:9781450334358
DOI:10.1145/2755996
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 24 June 2015

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Author Tags

  1. -1}-matrix
  2. 1
  3. homology
  4. linear system solving
  5. smith form
  6. sparse matrix
  7. {0

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