# Applications of Siegel's Lemma to a system of linear forms and its minimal points

## TL;DR

This paper provides a new proof and extension of bounds on approximation exponents for systems of linear forms, using Siegel's Lemma, with implications for understanding best approximation vectors and subspace approximation.

## Contribution

The paper introduces a new proof of a known bound on approximation exponents, extends results to higher dimensions, and establishes criteria for linear independence of best approximation vectors.

## Key findings

- Conditional bounds on approximation exponents for systems of linear forms.
- Unconditional confirmation of a special case for m=1, n=2.
- Criteria for linear independence of consecutive best approximation vectors.

## Abstract

Consider a real matrix $\Theta$ consisting of rows $(\theta_{i,1},\ldots,\theta_{i,n})$, for $1\leq i\leq m$. The problem of making the system linear forms $x_{1}\theta_{i,1}+\cdots+x_{n}\theta_{i,n}-y_{i}$ for integers $x_{j},y_{i}$ small naturally induces an ordinary and a uniform exponent of approximation, denoted by $w(\Theta)$ and $\widehat{w}(\Theta)$ respectively. For $m=1$, a sharp lower bound for the ratio $w(\Theta)/\widehat{w}(\Theta)$ was recently established by Marnat and Moshchevitin. We give a short, new proof of this result upon a hypothesis on the best approximation integer vectors associated to $\Theta$. Our conditional result extends to general $m>1$ (but may not be optimal in this case). Moreover, our hypothesis is always satisfied in particular for $m=1, n=2$ and thereby unconditionally confirms a previous observation of Jarn\'ik. We formulate our results in the more general context of approximation of subspaces of Euclidean spaces by lattices. We further establish criteria upon which a given number $\ell$ of consecutive best approximation vectors are linearly independent. Our method is based on Siegel's Lemma.