October: Quantum computing breakthrough | News and features

Researchers from the University of Bristol, Quantum Start, Phasecraft and Google Quantum AI have revealed properties of electronic systems that can be used to develop more efficient batteries and solar cells.

the findings, Published in Nature Communications Today, how the team has taken an important first step toward using quantum computers to determine the low-energy properties of highly correlated electronic systems that cannot be resolved by classical computers. They did this by developing the first truly scalable algorithm for observing the ground-state properties of the Fermi-Hubbard model on a quantum computer. The Fermi-Hubbard model is a means of discovering important insights into the 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 to develop more efficient solar cells and batteries, or even high-temperature superconductors. However, doing so is still beyond the capabilities of the world’s most powerful supercomputers. The Fermi-Hubbard model is widely known as an excellent benchmark for near-term quantum computers because it is the simplest material system that includes non-trivial correlations beyond what is captured by classical methods. Roughly producing the lowest-energy state (Earth) from the Fermi-Hubbard model enables the basic physical properties of the model to be calculated.

In the past, researchers only succeeded in solving very small and simplified Fermi-Hubbard states on a quantum computer. This research shows that it is possible to achieve more ambitious results. Leveraging a new highly efficient algorithm and better error mitigation techniques, they successfully conducted an experiment four times larger—consisting of ten times more quantum gates—than anything previously recorded.

“The Fermi-Hubbard example in this experiment represents a critical step towards solving real-world matter systems using a quantum computer,” said Professor of Quantum Computing at the University of Bristol. Ashley Montanaro and Phasecraft co-founder. “We succeeded by developing the first truly scalable algorithm that anyone could implement for the Fermi-Hubbard model. This is particularly exciting because it indicates that we will be able to extend our methods in order to take advantage of more powerful quantum computers as the hardware improves.”

Phasecraft brings together many of the world’s leading quantum scientists and engineers and partners with the world’s leading quantum device developers. Their research led to fundamental breakthroughs in quantum science and aims to drastically reduce the time scale of the quantum advantage in several critical areas. In addition to developing algorithms that will be able to scale to larger quantum computers, the Phasecraft team is also focused on continuing to build practically relevant features into their models so that they more accurately represent real-world systems.

“We are excited to see this experiment designed and implemented by Phasecraft, which represents one of the largest numerical fermion simulations to date, and also one of the largest variable algorithms to date, being performed on Google’s quantum computing hardware,” says Ryan Babush, head of Quantum Algorithms. In Google AI. “The scalability of their approach derives from being recent in terms of error mitigation and algorithm aggregation for near-term quantum devices.”

“This experiment represents a new milestone. It tells us what today’s quantum computers can do when we apply the best algorithmic technology available,” says Stasja Stanisic, senior quantum engineer at Phasecraft, lead author of the paper. “We can build on this work to develop better algorithms and better encodings for problems. the realism of today’s devices.”

The work was funded partly by ERC through Professor Ashley Montanaro’s Consolidator Grant “Quantitative Algorithms: From Institutions to Applications”, and partly by UKRI through the EPSRC Prosperity Partnership Programme, which enabled collaboration between partners.


Observing the ground state properties of a Fermi-Hubbard model using a scalable algorithm on a quantum computer by Stasja Stanisic and Ashley Montanaro et al in Nature Communications.

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