Title: Quantum Resonance Entanglement for Computational Geometry

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum Resonance Entanglement (QRE) presents a promising avenue for advancing computational geometry, offering the potential for dynamic, self-correcting geometric models with enhanced fidelity. This paper explores the application of QRE to geometric primitives, demonstrating a novel method for inducing and stabilizing entanglement between them. The core mechanism involves a feedback loop based on entanglement dynamics, continuously adjusting geometric parameters to mitigate error propagation and improve accuracy. We present a conceptual framework and preliminary results demonstrating the feasibility of this approach, highlighting its potential to surpass traditional methods in computational geometry tasks. This research contributes to a paradigm shift in geometric modeling by leveraging the unique properties of entanglement.

DOI: 10.5281/zenodo.22577702

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