Quantum computation of reactions on surfaces using local embedding

• Published in: npj quantum information Vol. 9; no. 1; pp. 88 - 10
• Main Authors: Gujarati, Tanvi P., Motta, Mario, Friedhoff, Triet Nguyen, Rice, Julia E., Nguyen, Nam, Barkoutsos, Panagiotis Kl, Thompson, Richard J., Smith, Tyler, Kagele, Marna, Brei, Mark, Jones, Barbara A., Williams, Kristen
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 12.09.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 639/301/1034/1038; 639/766/483/3926; Algorithms; Automation; Classical and Quantum Gravitation; Computers; Embedding; Magnesium; Materials science; Physics; Physics and Astronomy; Quantum Computing; Quantum Field Theories; Quantum Information Technology; Quantum Physics; Relativity Theory; Spintronics; String Theory
• ISSN: 2056-6387; 2056-6387
• DOI: 10.1038/s41534-023-00753-1

Modeling electronic systems is an important application for quantum computers. In the context of materials science, an important open problem is the computational description of chemical reactions on surfaces. In this work, we outline a workflow to model the adsorption and reaction of molecules on surfaces using quantum computing algorithms. We develop and compare two local embedding methods for the systematic determination of active spaces. These methods are automated and based on the physics of molecule-surface interactions and yield systematically improvable active spaces. Furthermore, to reduce the quantum resources required for the simulation of the selected active spaces using quantum algorithms, we introduce a technique for exact and automated circuit simplification. This technique is applicable to a broad class of quantum circuits and critical to enable demonstration on near-term quantum devices. We apply the proposed combination of active-space selection and circuit simplification to the dissociation of water on a magnesium surface using classical simulators and quantum hardware. Our study identifies reactions of molecules on surfaces, in conjunction with the proposed algorithmic workflow, as a promising research direction in the field of quantum computing applied to materials science.