Quantum Entanglement-Driven Geometric Phase Transitions

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum entanglement offers a powerful tool for understanding and predicting complex geometric phase transitions, a challenge largely addressed through traditional analytical methods. This paper proposes a novel algorithm leveraging quantum entanglement to rapidly assess phase transition points within dynamically evolving geometric systems. We demonstrate the effectiveness of this approach through a rigorous theoretical analysis and initial experimental validation, showcasing a significant improvement over existing correlation-based techniques. The core mechanism involves a quantum-enhanced evolution algorithm that dynamically modifies the geometric structure, enabling the detection of subtle phase transition signatures. This research moves beyond simple correlation analysis, offering a fundamentally different perspective on the dynamics of complex systems.

DOI: 10.5281/zenodo.22266132

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