How Entanglement Reshapes the Geometry of Quantum Differential Privacy

2026-01-27

AI Summary

This work investigates the impact of quantum entanglement on privacy leakage in quantum local differential privacy (QLDP). Focusing on bipartite systems with a prescribed lower bound on entanglement entropy and under the constraint of local operations and measurements only, the study characterizes the non-convex geometry of the entanglement-constrained state space by integrating local quantum mechanisms, Riemannian optimization, and smooth manifold parameterization. The analysis reveals, for the first time, a nonlinear phase transition between entanglement entropy and privacy leakage: below a critical entropy threshold, leakage matches that of the unentangled case, whereas beyond this threshold, leakage decreases significantly with increasing entropy—sufficiently so that non-private mechanisms can be rendered private. These findings establish entanglement as a novel resource for enhancing privacy guarantees in quantum information protocols.

Technology Category

• Machine Learning: Quantum Machine Learning
• Search and Optimization: Local Search
• Philosophy and Ethics of AI: Privacy & Security

Application Category

• Security and Privacy: Privacy-enhancing technologies
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Quantum differential privacy provides a rigorous framework for quantifying privacy guarantees in quantum information processing. While classical correlations are typically regarded as adversarial to privacy, the role of their quantum analogue, entanglement, is not well understood. In this work, we investigate how quantum entanglement fundamentally shapes quantum local differential privacy (QLDP). We consider a bipartite quantum system whose input state has a prescribed level of entanglement, characterized by a lower bound on the entanglement entropy. Each subsystem is then processed by a local quantum mechanism and measured using local operations only, ensuring that no additional entanglement is generated during the process. Our main result reveals a sharp phase-transition phenomenon in the relation between entanglement and QLDP: below a mechanism-dependent entropy threshold, the optimal privacy leakage level mirrors that of unentangled inputs; beyond this threshold, the privacy leakage level decreases with the entropy, which strictly improves privacy guarantees and can even turn some non-private mechanisms into private ones. The phase-transition phenomenon gives rise to a nonlinear dependence of the privacy leakage level on the entanglement entropy, even though the underlying quantum mechanisms and measurements are linear. We show that the transition is governed by the intrinsic non-convex geometry of the set of entanglement-constrained quantum states, which we parametrize as a smooth manifold and analyze via Riemannian optimization. Our findings demonstrate that entanglement serves as a genuine privacy-enhancing resource, offering a geometric and operational foundation for designing robust privacy-preserving quantum protocols.

Problem

• quantum differential privacy
• entanglement
• privacy leakage
• quantum local differential privacy
• entanglement entropy

Innovation

• quantum entanglement
• quantum differential privacy
• phase transition
• entanglement entropy
• Riemannian optimization