Quantum Algorithms for Materials Science: Studying quantum algorithms for chemistry and materials science applications

Authors

  • Dr. Daniel Gutiérrez Professor of Industrial Engineering, National Technological University (UTN), Argentina Author

Keywords:

Quantum computing, Quantum algorithms, Chemistry

Abstract

Quantum computing has emerged as a promising paradigm for tackling complex problems in chemistry and materials science that are intractable for classical computers. This paper provides an overview of quantum algorithms tailored for these fields, focusing on their potential to revolutionize molecular simulation, drug discovery, and material design. We discuss key quantum algorithms, such as the variational quantum eigensolver (VQE), quantum approximate optimization algorithm (QAOA), and quantum phase estimation (QPE), highlighting their principles and applications. Additionally, we explore quantum algorithms' current challenges and future prospects, emphasizing the need for continued research to realize their full potential.

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Published

14-06-2024

How to Cite

[1]
Dr. Daniel Gutiérrez, “Quantum Algorithms for Materials Science: Studying quantum algorithms for chemistry and materials science applications”, Distrib Learn Broad Appl Sci Res, vol. 10, pp. 72–79, Jun. 2024, Accessed: Dec. 22, 2024. [Online]. Available: https://dlabi.org/index.php/journal/article/view/52

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