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Quantum-Driven Lattice Parameter Optimization for Materials

Jincheng Zhang

Published Sep 2, 2026• 0 citations
Publisher

Abstract

Quantum-driven lattice parameter optimization is a novel approach to materials science that leverages the power of quantum computing to efficiently explore the parameter space of crystal structures. Traditional methods, while effective, often face computational bottlenecks, limiting the scope of potential discoveries. This paper proposes a quantum-enhanced optimization strategy utilizing quantum annealing and variational quantum eigensolver (VQE) techniques to systematically search for optimal lattice parameters, potentially leading to the identification of novel material properties. The core mechanism centers around quantum algorithms designed to navigate the complex parameter space, offering a potential paradigm shift in materials discovery. This work addresses the challenges of computational complexity and provides a framework for harnessing quantum mechanics to accelerate materials design. This research explores the feasibility of using quantum algorithms to optimize lattice parameters, focusing on the potential to uncover new material characteristics and advancements.

DOI
10.5281/zenodo.22252191

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