Chio Condensation and Random Sign Matrices
Peter Christian Heinig

TL;DR
This paper introduces a new measure related to Chio condensation for counting Z-singular matrices with ±1 entries, connecting it to known probability measures and graph properties, and explores its implications for matrix singularity probabilities.
Contribution
It defines a novel measure P_chio linked to Chio condensation, characterizes it graph-theoretically, and analyzes its independence properties and computational complexity.
Findings
P_chio closely relates to the uniform measure and lazy coin flip distribution.
Deciding equality of P_chio and P_lcf is computationally hard (Omega(n^2)).
P_chio exhibits k-wise independence properties.
Abstract
This is to suggest a new approach to the old and open problem of counting the number f_n of Z-singular n x n matrices with entries from {-1,+1}: Comparison of two measures, none of them the uniform measure, one of them closely related to it, the other asymptotically under control by a recent theorem of Bourgain, Vu and Wood. We will define a measure P_chio on the set {-1,0,+1}^([n-1]^2) of all (n-1)x(n-1)-matrices with entries from {-1,0,+1} which (owing to a determinant identity published by M. F. Chio in 1853) is closely related to the uniform measures on {-1,+1}^([n]^2) and {0,1}^([n-1]^2) and at the same time it intriguingly mimics the so-called lazy coin flip distribution P_lcf on {-1,0,+1}^([n-1]^2), with the resemblance fading more and more as the events get smaller. This is relevant in view of a recent theorem of J. Bourgain, V. H. Vu and P. M. Wood (J. Funct. Anal. 258…
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Taxonomy
TopicsGraph theory and applications · Random Matrices and Applications · Markov Chains and Monte Carlo Methods
