Quantum Entanglement Modeling Based on Tensor Categories: A Framework for Enhanced Quantum Information Manipulation
Jincheng Zhang
Quantum entanglement, a cornerstone of quantum mechanics, presents unique challenges to traditional modeling approaches. The non-locality inherent in entangled states complicates fundamental understanding and control. This paper proposes a novel framework, leveraging tensor categories, to address this challenge, aiming to model and manipulate entanglement with enhanced precision. We construct a model that dynamically adjusts entangled states, utilizing tensor categories to encapsulate the non-locality inherent in the system. This approach offers a more intuitive and controllable way to operate on quantum information, potentially unlocking new computational capabilities. The core claim is that this framework provides a fundamental shift in our understanding and manipulation of entangled states, enabling novel quantum algorithms and information processing techniques. The work explores the potential of tensor categories to represent and manipulate entanglement, leading to a more robust and insightful model of quantum phenomena.
•Aug 31, 2026•0 citations