Michel H. Devoret was one of three physicists who won this year’s Nobel Prize in Physics for a series of experiments they conducted more than four decades ago.
As a postdoctoral researcher at the University of California, Berkeley, in the mid-1980s, Dr. Devoret helped show that the strange and powerful properties of quantum mechanics — the physics of the subatomic realm — could also be observed in electrical circuits large enough to be seen with the naked eye.
That discovery, which paved the way for cellphones and fiber-optic cables, may have greater implications in the coming years as researchers build quantum computers that could be vastly more powerful than today’s computing systems. That could lead to the discovery of new medicines and vaccines, as well as cracking the encryption techniques that guard the world’s secrets.
On Wednesday, Dr. Devoret and his colleagues at a Google lab near Santa Barbara, Calif., said their quantum computer had successfully run a new algorithm capable of accelerating advances in drug discovery, the design of new building materials and other fields.
Leveraging the counterintuitive powers of quantum mechanics, Google’s machine ran this algorithm 13,000 times as fast as a top supercomputer executing similar code in the realm of classical physics, according to a paper written by the Google researchers in the scientific journal Nature.
“In the future when we have bigger quantum computers, we will be able to run calculations that would be impossible with classical algorithms,” said Dr. Devoret, who joined Google in 2023.
Quantum computing is still an experimental technology. But Google’s new algorithm, Quantum Echoes, shows that scientists are rapidly improving techniques that could allow quantum computers to crack scientific problems no traditional computing device ever could.
“It’s a meaningful technological advance,” said Prineha Narang, a professor of physical sciences and electrical and computer engineering at the University of California, Los Angeles. “We have heard a lot about hardware advances in the field, and for a while, I worried that the algorithms would not keep up. But they have shown that this is not the case.”
Google’s quantum research is competing with other tech giants like Microsoft and IBM, myriad start-ups, universities and rapidly advancing efforts in China. The Chinese government has committed more than $15.2 billion to quantum research.
Inside a classical computer like a laptop or a smartphone, silicon chips store numbers as “bits” of information. Each bit holds either a 1 or a 0. The chips then perform calculations by manipulating these bits — adding them, multiplying them and so on.
A quantum computer, by contrast, performs calculations in ways that defy common sense.
According to the laws of quantum mechanics — the physics of very small things — a single object can behave like two separate objects at the same time. By exploiting this strange phenomenon, scientists can build quantum bits, or “qubits,” that hold a combination of 1 and 0 at the same time.
This means that as the number of qubits grows, a quantum computer becomes exponentially more powerful.
With two other researchers at Berkeley in the mid-1980s, John M. Martinis and John Clarke, Dr. Devoret showed that the counterintuitive properties of quantum mechanics were not limited to subatomic particles. They also appeared in electrical circuits that could be used to build computer chips.
“We showed for the first time that you could build atoms out of electrical circuits,” Dr. Devoret said.
The discovery laid the foundation for the “superconducting qubits” that Google, IBM and many other companies use to power their quantum computers. This involves cooling certain metals to extremely low temperatures so they exhibit the same strange behavior as subatomic particles.
Today’s quantum computers still make too many mistakes. But thanks to recent advances in error correction — a way of reducing mistakes — many scientists now believe the technology can live up to its promise by around the end of the decade.
Google announced last year that it had built a quantum computer that needed less than five minutes to perform a particularly complex mathematical calculation in a test designed to gauge the progress of the technology. One of the world’s most powerful non-quantum supercomputers would not have been able to complete it in 10 septillion years, a length of time that exceeds the age of the known universe by billions of trillions of years.
This moment of “quantum supremacy” showed that the technology was beginning to push beyond the powers of classical computers. But the calculation performed by Google’s machine, based on a chip called Willow, had no practical use.
Google and its many rivals are still working toward the moment when a quantum computer can surpass what is possible with a classical computer as it performs important tasks in fields like chemistry and artificial intelligence.
“For the promise of quantum computers to be unlocked, we need to produce a new drug that we only know about because of quantum computers,” Dr. Narang of U.C.L.A. said. “Then you can say that all the investment was worthwhile.”
Google’s new algorithm is a step in that direction. In another paper published on Wednesday on the research site arXiv, the company showed that its algorithm could help improve what is called nuclear magnetic resonance, or N.M.R., which is a technique used to understand the structure of tiny molecules and how they interact with one another.
N.M.R. is a vital part of effort to develop new medicines for fighting disease and new materials for building everything from cars to buildings. It can help understand Alzheimer’s disease or drive the creation of entirely new metals, said Ashok Ajoy, an assistant professor of chemistry at Berkeley who specializes in N.M.R. and worked with Google’s researchers on the new paper.
“This illustrates the power of a quantum computer,” he said. “It is still early days. But the prospects are exciting.”
Cade Metz is a Times reporter who writes about artificial intelligence, driverless cars, robotics, virtual reality and other emerging areas of technology.
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