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A matrix version of the Steinitz lemma

Imre Barany

Abstract

The Steinitz lemma, a classic from 1913, states that $a_1,\ldots,a_n$, a sequence of vectors in $\R^d$ with $\sum_1^n a_i=0$, can be rearranged so that every partial sum of the rearranged sequence has norm at most $2d\max \|a_i\|$. In the matrix version $A$ is a $k\times n$ matrix with entries $a_i^j \in \R^d$ with $\sum_{j=1}^k\sum_{i=1}^na_i^j=0$. It is proved in \cite{OPW} that there is a rearrangement of row $j$ of $A$ (for every $j$) such that the sum of the entries in the first $m$ columns of the rearranged matrix has norm at most $40d^5\max \|a_i^j\|$ (for every $m$). We improve this bound to $(4d-2)\max \|a_i^j\|$.

A matrix version of the Steinitz lemma

Abstract

The Steinitz lemma, a classic from 1913, states that , a sequence of vectors in with , can be rearranged so that every partial sum of the rearranged sequence has norm at most . In the matrix version is a matrix with entries with . It is proved in \cite{OPW} that there is a rearrangement of row of (for every ) such that the sum of the entries in the first columns of the rearranged matrix has norm at most (for every ). We improve this bound to .
Paper Structure (5 sections, 6 theorems, 13 equations)

This paper contains 5 sections, 6 theorems, 13 equations.

Key Result

Theorem 1.1

For every $A \in \mathcal{A}(K)$ with $\sigma_n(A)=0$ there is a row-permuted copy, $C$, of $A$ such that

Theorems & Definitions (6)

  • Theorem 1.1
  • Theorem 1.2
  • Theorem 1.3
  • Theorem 2.1
  • Lemma 2.1
  • Theorem 2.2