Complexity for exact polynomial optimization strengthened with Fritz John conditions

Let $f,g_1,\dots,g_m$ be polynomials of degree at most $d$ with real coefficients in a vector of variables $x=(x_1,\dots,x_n)$. Assume that $f$ is non-negative on a basic semi-algebraic set $S$ defined by polynomial inequalities $g_j(x)\ge 0$, for $j=1,\dots,m$. Our previous work [arXiv:2205.04254 (2022)] has stated several representations of $f$ based on the Fritz John conditions. This paper provides some explicit degree bounds depending on $n$, $m$, and $d$ for these representations. In application to polynomial optimization, we obtain explicit rates of finite convergence of the hierarchies of semidefinite relaxations based on these representations.