Quantum Information Entropy: A Theoretical Computation Framework

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum information entropy, a fundamental measure of uncertainty, is a complex concept that has long evaded direct computational analysis. This paper introduces a novel theoretical framework for calculating quantum information entropy, leveraging the principles of quantum entanglement and quantum algorithms to achieve precise and efficient computation. We present a new algorithm, the "Entangled Entropy Accelerator" (TEA), designed to exploit quantum entanglement to significantly accelerate entropy calculations compared to classical methods. The core mechanism of the TEA centers around the application of a tailored quantum algorithm to a specific type of quantum data, effectively reducing the computational complexity. The resultant framework offers a robust and scalable method for quantifying and analyzing quantum information entropy. This research demonstrates the potential of quantum computation to unlock new insights into the nature of information and its underlying dynamics.

DOI: 10.5281/zenodo.22496170

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