# On rank-critical matrix spaces

## TL;DR

This paper provides a complete characterization of rank-critical matrix spaces over large fields, including conditions for their decomposition and the rank-criticality of their direct sums, advancing understanding in linear algebra and matrix theory.

## Contribution

It introduces a necessary and sufficient condition for rank-criticality of matrix spaces over large fields and analyzes their decomposition and direct sum properties.

## Key findings

- Characterization of rank-critical matrix spaces over large fields
- Decomposition of rank-critical spaces into compression and primitive parts
- Rank-criticality of block-diagonal sums depends on primitivity

## Abstract

A matrix space of size $m\times n$ is a linear subspace of the linear space of $m\times n$ matrices over a field $\mathbb{F}$. The rank of a matrix space is defined as the maximal rank over matrices in this space. A matrix space $\mathcal{A}$ is called rank-critical, if any matrix space which properly contains it has rank strictly greater than that of $\mathcal{A}$. In this note, we first exhibit a necessary and sufficient condition for a matrix space $\mathcal{A}$ to be rank-critical, when $\mathbb{F}$ is large enough. This immediately implies the sufficient condition for a matrix space to be rank-critical by Draisma (Bull. Lond. Math. Soc. 38(5):764--776, 2006), albeit requiring the field to be slightly larger. We then study rank-critical spaces in the context of compression and primitive matrix spaces. We first show that every rank-critical matrix space can be decomposed into a rank-critical compression matrix space and a rank-critical primitive matrix space. We then prove, using our necessary and sufficient condition, that the block-diagonal direct sum of two rank-critical matrix spaces is rank-critical if and only if both matrix spaces are primitive, when the field is large enough.