Nuclear Magnetic Resonance or NMR spectroscopy is a technique used to understand the structure of tiny molecules and how they interact with one another. Crucial in the development of new materials and medicines, it is a mainstay of chemical and biological research. In Alzheimer’s disease research, for example, it is used to identify biomarkers and measure brain atrophy.
Now, researchers at Google Quantum AI have successfully used the Willow quantum chip to interpret data from NMR spectroscopy. The algorithm ran on a Willow quantum-computer chip that can outperform classical supercomputers, at least for specific benchmark tasks. It also ran 13,000 times faster than would have been possible on the world’s best supercomputer.
The new algorithm, named Quantum Echoes, has been detailed in a paper published in Nature this month. “It can explain interactions between atoms in a molecule using nuclear magnetic resonance, paving a path towards future uses in drug discovery and materials science,” wrote Google CEO Sundar Pichai on X.
The search engine giant is calling its demonstration an example of “quantum advantage”, or the point at which quantum systems gain a clear lead over traditional computers. Quantum Echoes is verifiable, that is, the results can be replicated on another quantum computer. Verifiable data also means that it can lead to practical applications.
“This repeatable, beyond-classical computation is the basis for scalable verification, bringing quantum computers closer to becoming tools for practical applications,” said Hartmut Neven, founder and lead, Google Quantum AI.
The new work is built on decades of research by Michel Devoret, chief scientist at Google’s quantum AI unit, who won the Nobel Prize for Physics this month, along with John Martinis and John Clarke. He said the event was a milestone in his field. “This marks a new step towards full-scale quantum computation,” Devoret added.
In a second paper, the company recorded how its algorithm could help improve NMR spectroscopy.
“Nuclear Magnetic Resonance — the spectroscopic cousin of MRI — reveals molecular structure by detecting the tiny magnetic ‘spins’ at the centres of atoms. Google’s Quantum Echoes algorithm showcases the potential for quantum computers to efficiently model and unravel the intricate interactions of these spins, possibly even across long distances. As quantum computing continues to mature, such approaches could enhance NMR spectroscopy, adding to its powerful toolbox for drug discovery and the design of advanced materials,” said Ashok Ajoy, collaborator with Google Quantum AI, and assistant professor of chemistry, UC Berkeley, US.
Last year, Google announced that Willow performed a standard benchmark computation in under five minutes that would take one of today’s fastest supercomputers 10 septillion years. One septillion equals one followed by 24 zeros.
In quantum computers, tiny circuits perform calculations parallelly, rather than sequentially, making them much faster. The Willow, for example, has 105 superconducting circuits.
The development brings Google a step closer to utilising the processing power promised by quantum computing, a technology that’s also being pursued by rivals Microsoft, International Business Machines (IBM) and some startups.
This demonstration of the “first-ever verifiable quantum advantage” with Quantum Echoes algorithm marks a “significant step toward the first real-world applications of quantum computing”, said the team at Google Quantum AI. Many experts, however, caution that practical impact remains many years away.
“With Quantum Echoes, we continue to be optimistic that within five years we’ll see real-world applications that are possible only on quantum computers,” Neven said. Researchers from IBM recently predicted that between now and the end of 2026, the quantum community will have uncovered the first quantum advantages.