Quantum Computing and Simulations for Energy Applications: Review and Perspective

• Published in: ACS Engineering Au Vol. 2; no. 3; pp. 151 - 196
• Main Authors: Paudel, Hari P., Syamlal, Madhava, Crawford, Scott E., Lee, Yueh-Lin, Shugayev, Roman A., Lu, Ping, Ohodnicki, Paul R., Mollot, Darren, Duan, Yuhua
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 15.06.2022
• Subjects: quantum computing; quantum entanglement and superposition; quantum information science; quantum networking and communications; quantum sensor; quantum simulation; Quantum information science; Quantum computing; Quantum networking and communications; Quantum entanglement and superposition; Quantum sensor; Quantum simulation
• ISSN: 2694-2488; 2694-2488
• DOI: 10.1021/acsengineeringau.1c00033

Quantum computing and simulations are creating transformative opportunities by exploiting the principles of quantum mechanics in new ways to generate and process information. It is expected that a variety of areas ranging from day-to-day activities to making advanced scientific discoveries are going to benefit from such computations. Several early stage applications of quantum computing and simulation have already been demonstrated, and these preliminary results show that quantum computing and simulations could significantly accelerate the deployment of new technologies urgently needed to meet the growing demand for energy while safeguarding the environment. Exciting examples include developing new materials such as alloys, catalysts, oxygen carriers, CO2 sorbents/solvents, and energy storage materials; optimizing traffic flows and energy supply chains; locating energy generation facilities such as wind and solar farms and fossil and nuclear power plants; designing pipeline networks for transporting hydrogen, natural gas, and CO2; and speeding up tasks such as seismic imaging and inversion, reservoir simulation, and computational fluid dynamics. In this review, we introduce different aspects of quantum computing and simulations and discuss the status of theoretical and experimental approaches. We then specifically highlight a growing number of application areas in the energy sector. We conclude by providing an analysis of high-value application directions to address energy sector challenges.