[guided]The previous step showed that monomial constraints force $\operatorname{Log}(\hat{K}_\Omega) \subset \operatorname{conv}(L)$. This step proves the reverse inclusion: every point $z \in \Omega$ whose logarithmic image $s = (\log|z_1|, \dots, \log|z_n|)$ lies in $\operatorname{conv}(L) \cap \operatorname{Log}(\Omega)$ belongs to $\hat{K}_\Omega$. To show $z \in \hat{K}_\Omega$, we must verify that $|f(z)| \leq \sup_K |f|$ for every $f \in \mathcal{O}(\Omega)$.
Why are monomials sufficient to determine the hull? Because on a logarithmically convex Reinhardt domain, the Laurent expansion expresses every [holomorphic function](/page/Holomorphic%20Function) as a convergent sum of monomials, and the monomial constraints from the previous step pass to arbitrary holomorphic functions by approximation.
Since $\Omega$ is a logarithmically convex Reinhardt domain, by the [Domains of Holomorphy Among Reinhardt Domains](/theorems/3394) it is a domain of holomorphy, and by the [Laurent Series in Complete Reinhardt Domains](/theorems/3419) every $f \in \mathcal{O}(\Omega)$ has a [Laurent series](/page/Laurent%20Series) expansion
\begin{align*}
f(z) = \sum_{\alpha \in \mathbb{Z}^n} a_\alpha z^\alpha
\end{align*}
converging absolutely and uniformly on compact subsets of $\Omega \cap (\mathbb{C}^*)^n$. The partial sums
\begin{align*}
S_N(z) = \sum_{|\alpha| \leq N} a_\alpha z^\alpha
\end{align*}
are Laurent polynomials. Since $K$ is compact in $\Omega$, the convergence $S_N \to f$ is uniform on $K$, so $\sup_K |S_N| \to \sup_K |f|$ and $S_N(z) \to f(z)$ pointwise.
Now we show that the monomial constraints pass to Laurent polynomials. Each $S_N$ is a finite linear combination of monomials $z^\alpha$. For each such monomial, the previous step established $|z^\alpha| \leq \sup_K |z^\alpha|$ (equivalently $\alpha \cdot s \leq \sup_{p \in L} \alpha \cdot p$) whenever $s \in \operatorname{conv}(L)$.
The sharper argument uses the torus invariance of $K$: since $K$ is torus-invariant, the [maximum modulus principle](/theorems/491) on torus orbits gives $|S_N(z)| \leq \sup_K |S_N|$ directly for each $N$. On each torus orbit $\{(\zeta_1, \dots, \zeta_n) : |\zeta_j| = |z_j|\}$, the Laurent polynomial $S_N$ restricted to the torus attains its maximum modulus on the boundary of $K$'s intersection with that torus orbit, and since $K$ is torus-invariant, this maximum is $\sup_K |S_N|$.
Taking $N \to \infty$: the [uniform convergence](/page/Uniform%20Convergence) $S_N \to f$ on $K$ gives $\sup_K |S_N| \to \sup_K |f|$, and pointwise convergence gives $S_N(z) \to f(z)$. Since $|S_N(z)| \leq \sup_K |S_N|$ for each $N$, passing to the limit yields $|f(z)| \leq \sup_K |f|$.
Therefore $z \in \hat{K}_\Omega$, and the holomorphic hull is exactly the Reinhardt domain whose logarithmic image is $\operatorname{conv}(L) \cap \operatorname{Log}(\Omega)$.
This is an instance of a general principle: when a domain has a large symmetry group (here, the torus $\mathbb{T}^n$), the holomorphic hull can be computed using a smaller class of "equivariant" functions (here, monomials). The torus symmetry decomposes $\mathcal{O}(\Omega)$ into weight spaces indexed by $\alpha \in \mathbb{Z}^n$, each one-dimensional (spanned by $z^\alpha$). The analogy with convex geometry is exact: the holomorphic hull of $K$ in $\Omega$ corresponds to the convex hull of $L$ in $\operatorname{Log}(\Omega)$, with monomials playing the role of linear functionals and the [maximum modulus principle](/page/Maximum%20Modulus%20Principle) playing the role of the hyperplane separation theorem.[/guided]