Quantum computing and materials science : a practical guide to applying quantum annealing to the configurational analysis of materials

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Camino, B. and Buckeridge, J. and Warburton, P. A. and Kendon, V. and Woodley, S. M. (2023) Quantum computing and materials science : a practical guide to applying quantum annealing to the configurational analysis of materials. Journal of Applied Physics, 133 (22). 221102. ISSN 0021-8979 (https://doi.org/10.1063/5.0151346)

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Abstract

Using quantum computers for computational chemistry and materials science will enable us to tackle problems that are intractable on classical computers. In this paper, we show how the relative energy of defective graphene structures can be calculated by using a quantum annealer. This simple system is used to guide the reader through the steps needed to translate a chemical structure (a set of atoms) and energy model to a representation that can be implemented on quantum annealers (a set of qubits). We discuss in detail how different energy contributions can be included in the model and what their effect is on the final result. The code used to run the simulation on D-Wave quantum annealers is made available as a Jupyter Notebook. This Tutorial was designed to be a quick-start guide for the computational chemists interested in running their first quantum annealing simulations. The methodology outlined in this paper represents the foundation for simulating more complex systems, such as solid solutions and disordered systems.

ORCID iDs

Camino, B., Buckeridge, J., Warburton, P. A., Kendon, V. ORCID logoORCID: https://orcid.org/0000-0002-6551-3056 and Woodley, S. M.;
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