Quantum Entanglement-Based Probabilistic Extension
Jincheng Zhang
Abstract
This paper explores a novel probabilistic extension to quantum mechanics, leveraging the unique properties of quantum entanglement to enhance prediction accuracy. Traditional probabilistic approaches often struggle with complex scenarios, necessitating computationally intensive calculations. This work proposes a method that dynamically adjusts probability estimates based on entangled correlations, offering a significant advancement in predictive capability. We detail the core mechanism, illustrating its potential for improved accuracy in scenarios demanding precise probabilistic assessment. The paper concludes with a discussion of future research directions, emphasizing the practical implications of this approach.