Quantum Information in Chemical Reaction Rate Prediction

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum information has emerged as a transformative tool across diverse fields, and its potential within chemical reaction rate prediction is increasingly attracting attention. This paper explores the integration of quantum information and geometric modeling to enhance the prediction of reaction rates, utilizing geometric information for optimization. We present a novel framework that leverages quantum algorithms to represent chemical reaction dynamics as geometric functions, enabling the optimization of reaction conditions based on these geometric representations. The core mechanism focuses on translating complex reaction kinetics into a simplified geometric model, allowing for efficient optimization through geometric analysis. The study demonstrates the effectiveness of this approach in predicting reaction rates, offering a promising pathway towards improved reaction control and understanding.

DOI: 10.5281/zenodo.22185230

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