Tensor Network Renormalization Optimization for Quantum Entanglement Entropy Calculation

Abstract

In the current era of quantum computing advancement, efficient calculation of quantum entanglement entropy is pivotal for understanding complex quantum systems. This study introduces an optimized tensor network renormalization technique that improves accuracy and computational efficiency. By leveraging advanced algebraic structures and state-of-the-art computational frameworks, our approach allows for precise manipulation of large-scale quantum data. The results demonstrate significant advancements in entropy calculation methods, paving the way for novel insights into quantum phase transitions.