Strong Polarization and Entropy
This work provides a technical generalization of a known inequality, offering incremental theoretical advances for researchers in convex geometry and functional analysis.
The authors prove a weighted strong polarization inequality for unit vectors in Hilbert spaces, which generalizes the recent solution to the strong polarization conjecture. The result yields a polarization inequality for products of powers of linear functionals and strengthens Bang's plank theorem, with applications to Shannon entropy in random sensing.
We show that for any set of $n$ unit vectors $v_1,\ldots,v_n$ in a real Hilbert space and positive numbers $p_1,\ldots,p_n$ satisfying $\sum_j p_j = 1$, there exists a unit vector $u$ such that \[ \sum_{j=1}^n \frac{p_j^2}{\langle v_j, u\rangle^2}\leq 1. \] This inequality is a weighted version of the strong polarization inequality. As immediate corollaries, it yields a polarization inequality for products of powers of linear functionals and a strengthening of Bang's classical plank theorem for Hilbert spaces. The proof follows the approach introduced by Martínez and Ortega-Moreno in their recent solution to the strong polarization conjecture posed by Ball and Frenkel. We further note that our weighted inequality admits a Shannon-entropy interpretation: in a random sensing model, the entropy of the weights controls the minimum expected logarithmic loss.