# Computing rational points in convex semi-algebraic sets and SOS decompositions

## TL;DR

This paper presents an algorithm to find rational points in convex semi-algebraic sets and applies it to decide sum of squares decompositions of polynomials, with complexity bounds depending on degrees and bit lengths.

## Contribution

It introduces a new algorithm for rational point finding in convex semi-algebraic sets and uses it to decide sum of squares decompositions efficiently.

## Key findings

- Algorithm finds rational points if they exist within specified complexity bounds.
- Procedure decides sum of squares decomposition with explicit complexity estimates.
- Output polynomials have coefficients with bounded bit length.

## Abstract

Let ${\cal P}=\{h_1, ..., h_s\}\subset \Z[Y_1, ..., Y_k]$, $D\geq \deg(h_i)$ for $1\leq i \leq s$, $\sigma$ bounding the bit length of the coefficients of the $h_i$'s, and $\Phi$ be a quantifier-free ${\cal P}$-formula defining a convex semi-algebraic set. We design an algorithm returning a rational point in ${\cal S}$ if and only if ${\cal S}\cap \Q\neq\emptyset$. It requires $\sigma^{\bigO(1)}D^{\bigO(k^3)}$ bit operations. If a rational point is outputted its coordinates have bit length dominated by $\sigma D^{\bigO(k^3)}$. Using this result, we obtain a procedure deciding if a polynomial $f\in \Z[X_1, >..., X_n]$ is a sum of squares of polynomials in $\Q[X_1, ..., X_n]$. Denote by $d$ the degree of $f$, $\tau$ the maximum bit length of the coefficients in $f$, $D={{n+d}\choose{n}}$ and $k\leq D(D+1)-{{n+2d}\choose{n}}$. This procedure requires $\tau^{\bigO(1)}D^{\bigO(k^3)}$ bit operations and the coefficients of the outputted polynomials have bit length dominated by $\tau D^{\bigO(k^3)}$.