Quantum-Entangled Probability Field Calibration
Jincheng Zhang
Abstract
This paper presents a novel approach to calibrating quantum probability fields, utilizing entanglement to achieve precise control and prediction of probabilistic outcomes. The core mechanism centers around a dynamically evolving entanglement network designed to measure and refine the probability distribution of a system, capitalizing on the inherent correlations of entangled particles. This system offers a pathway to quantum-enhanced prediction, surpassing conventional measurement techniques by directly manipulating probability distributions. The resulting framework provides a foundation for advanced quantum simulations and control, potentially revolutionizing fields reliant on probabilistic outcomes.