Quantum Entanglement and Probability Logic: An Algorithm Optimization Approach

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum entanglement, a bizarre phenomenon in quantum mechanics, has captivated researchers and intrigued theorists alike. Harnessing this unique property offers the potential for revolutionary computing paradigms. This paper explores the application of probability logic to quantum entanglement, proposing a novel algorithm optimization approach that leverages probabilistic mechanisms to enhance the efficiency of quantum computation and algorithmic processes. We introduce a probabilistic approach to parameter optimization within the context of entangled states, aiming to improve the performance of quantum algorithms. The core claim is that this method, when applied to quantum entanglement, can significantly boost algorithm efficiency compared to traditional numerical methods. The research focuses on a mechanism that dynamically adjusts the probabilities associated with different quantum states, thereby guiding the evolution of parameters towards optimal solutions.

DOI: 10.5281/zenodo.22254286

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