Quantum Entanglement Simulation: A Quantum Information Adaptive Algorithm

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum entanglement, a fundamental aspect of quantum mechanics, offers a unique platform for simulating complex quantum systems. Traditional computational methods struggle to effectively handle these intricate systems, often requiring exponentially increasing computational resources. This paper introduces a novel quantum information adaptive algorithm based on the principles of quantum entanglement. The algorithm leverages the fragility of entanglement to dynamically adjust simulation parameters based on the outcome of the simulation, thereby enabling automated parameterization and optimization, significantly reducing computational cost. We present a detailed explanation of the core mechanism, including the mathematical formulation of the entanglement-based feedback loop and its impact on the simulation process. This research explores the potential of this approach to revolutionize quantum simulation, offering a pathway towards more efficient and adaptable simulations of complex quantum systems.

DOI: 10.5281/zenodo.22263296

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