Research reveals how quantum computing can simulate materials
Researchers have developed quantum algorithms to simulate the catalysts used in many industrial chemical processes, promising to reduce the environmental impact of fuel cells, petrochemicals and hydrogen production. The research, undertaken by Riverlane and Johnson Matthey, was published in Physical Review Research. The paper demonstrates how an error-corrected quantum computer can simulate nickel oxide and palladium oxide, important materials in heterogeneous catalysis, a process used to create a broad range of chemicals and fuels.
Dr Aleksei Ivanov, a quantum scientist at Riverlane and the paper’s lead author, commented: “Our algorithm enables the quantum simulation of large solid-state systems with runtimes often associated with much smaller molecular systems. This work paves the way towards future practical simulations of materials on error-corrected quantum computers.”
Some materials are challenging to simulate on ordinary computers due to their complex, quantum nature. This is where quantum computers can help, but until now, most of the research has focused on the simulation of molecules, not materials. Dr Rachel Kerber, Senior Scientist at Johnson Matthey, added: “Quantum simulations could provide a means for us to model many of these materials, which are often of great interest to researchers in catalysis and materials science in general."
The researchers leveraged concepts developed in classical computational condensed matter research to develop the new quantum algorithm.
Dr Christoph Sunderhauf, Senior Quantum scientist at Riverlane and the paper’s co-author, said: “In this work, we asked ourselves: How can we modify an existing molecular algorithm to take advantage of the material’s structure? We figured out how to do this and, as a result, our modifications to the existing quantum algorithm reduce the quantum resource requirements. So, future quantum computers require far fewer qubits and a reduced circuit depth, compared to when prior quantum algorithms without any modification. The main caveat here is that we will have to wait until someone actually builds a sufficiently large error-corrected quantum computer.”
Today’s quantum computers have a few hundred quantum bits (qubits), at most, limiting the usefulness of these machines. But quantum computers must scale up by orders of magnitude to reach error correction and unlock applications across multiple industries.
To reach error correction sooner, Riverlane is building the operating system for error-corrected quantum computers, which includes a control system (to control and calibrate the millions of qubits required) and fast decoders (to stop errors propagating and rendering calculations useless).
When these error-corrected quantum computers are ready, we also need fault-tolerant quantum algorithms to be ready to run on these machines. Ivanov added: “We need to strive to unlock useful application cases of quantum computers. If we continue to improve quantum algorithms further, then we wouldn’t need to build such a huge quantum computer for useful applications.”