Phasecraft has achieved a milestone for quantum computing research, bringing quantum theory from research to reality, faster, according to a company news release. A team of Phasecraft researchers led by company co-founder Ashley Montanaro developed and tested algorithms to optimize and predict the quantum hardware capacity needed to run meaningful programs, solving complex problems beyond the realms of classical computing.
The Fermi-Hubbard model is of fundamental importance in condensed-matter physics as a model for strongly correlated materials and a route to understanding high-temperature superconductivity. Finding the ground state of the Fermi-Hubbard model has been predicted to be one of the first applications of near-term quantum computers, and one that offers a pathway to understanding and developing novel materials.
Montanaro, research lead and cofounder of Phasecraft, said the research may bring quantum computing closer to reality.
“Quantum computing has critically important applications in materials science and other domains. Despite the major quantum hardware advances recently, we may still be several years from having the right software and hardware to solve meaningful problems with quantum computing,” said Montanaro. “Our research focuses on algorithms and software optimizations to maximize the quantum hardware’s capacity, and bring quantum computing closer to reality.”
“Near-term quantum hardware will have limited device and computation size. Phasecraft applied new theoretical ideas and numerical experiments to put together a very comprehensive study on different strategies for solving the Fermi-Hubbard model, zeroing in on strategies that are most likely to have the best results and impact in the near future.”
Montanaro added that the research applied theory and experiments.
“Near-term quantum hardware will have limited device and computation size,” Montanaro said. “Phasecraft applied new theoretical ideas and numerical experiments to put together a very comprehensive study on different strategies for solving the Fermi-Hubbard model, zeroing in on strategies that are most likely to have the best results and impact in the near future.”
According to the researchers, the results suggest future promise for quantum computers.
“The results suggest that optimizing over quantum circuits with a gate depth substantially less than a thousand could be sufficient to solve instances of the Fermi-Hubbard model beyond the capacity of a supercomputer,” said Montanaro. “This new research shows significant promise for the capabilities of near-term quantum devices, improving on previous research findings by around a factor of 10.”
The peer-reviewed research paper is featured in Physical Review B, published by the American Physical Society, the top specialist journal in condensed-matter physics. It was also chosen as an Editors’ Suggestion and to appear in Physics magazine.
Since it was founded in 2019, Phasecraft has established itself as an emerging leader in quantum research. Started by leading quantum scientists Montanaro, Toby Cubitt and John Morton, Phasecraft has built a team to enable near-term applications of quantum computing by developing high-efficiency algorithms to optimize the capabilities of near-term quantum hardware.
Phasecraft has closed a record seed round for a quantum company in the UK with £3.7 million in funding from private-sector VC investors, led by LocalGlobe with Episode1 along with previous investors. Former Songkick founder Ian Hogarth has also joined as board chair for Phasecraft. Phasecraft previously raised a £750,000 pre-seed round led by UCL Technology Fund with Parkwalk Advisors and London Co-investment Fund and has earned several grants facilitated by InnovateUK. Between equity funding and research grants, Phasecraft has raised more than £5.5 million.
Cubitt noted the importance of the funding.
“With new funding and support, we are able to continue our pioneering research and industry collaborations to develop the quantum computing industry and find useful applications faster,” said Cubitt.