Researchers from the University of Bristol, quantum start-up, Phasecraft and Google Quantum AI have revealed properties of electronic systems that could be used for the development of more efficient batteries and solar cells.
October 11, 2022
Researchers from the University of Bristol, quantum start-up, Phasecraft and Google Quantum AI have revealed properties of electronic systems that could be used for the development of more efficient batteries and solar cells.
The findings, published in Nature Communications today, describes how the team has taken an important first step towards using quantum computers to determine low-energy properties of strongly-correlated electronic systems that cannot be solved by classical computers. They did this by developing the first truly scalable algorithm for observing ground-state properties of the Fermi-Hubbard model on a quantum computer. The Fermi-Hubbard model is way of discovering crucial insights into electronic and magnetic properties of materials.
Modeling quantum systems of this form has significant practical implications, including the design of new materials that could be used in the development of more effective solar cells and batteries, or even high-temperature superconductors. However, doing so remains beyond the capacity of the world’s most powerful supercomputers. The Fermi-Hubbard model is widely recognized as an excellent benchmark for near-term quantum computers because it is the simplest materials system that includes non-trivial correlations beyond what is captured by classical methods.
