Geometric Optimization for Tight Entropic Uncertainty Relations

TL;DR

This paper introduces a geometric optimization approach to derive tight entropic uncertainty relations for general quantum measurements, improving bounds and practical applications in quantum information tasks.

Contribution

It reformulates the problem as a geometric optimization, providing an effective method for tight bounds in finite-dimensional quantum systems.

Findings

Yields tight entropic uncertainty bounds with numerical precision.

Outperforms existing analytical and majorization bounds.

Demonstrates advantages in quantum steering applications.

Abstract

Entropic uncertainty relations play a fundamental role in quantum information theory. However, determining optimal (tight) entropic uncertainty relations for general observables remains a formidable challenge and has so far been achieved only in a few special cases. Motivated by Schwonnek \emph{et al.} [PRL \textbf{119}, 170404 (2017)], we recast this task as a geometric optimization problem over the quantum probability space. This procedure leads to an effective outer-approximation method that yields tight entropic uncertainty bounds for general measurements in finite-dimensional quantum systems with preassigned numerical precision. We benchmark our approach against existing analytical and majorization-based bounds, and demonstrate its practical advantage through applications to quantum steering.