Credit: Google
Google has announced that its latest quantum computing system, “Willow,” delivers unprecedented performance on a quantum benchmark and has made significant advances in error correction:
- Willow can reduce errors “exponentially as the system scales up using more qubits. “This cracks a challenge in quantum error correction that the field has pursued for almost 30 years,” said Hartmut Neven, founder and lead, Google Quantum AI, in a blog.
- The system, Neven said, performed a computation on the random circuits sampling (RCS) benchmark in under five minutes that would take one of today’s fastest exascale supercomputers 10 septillion (1025) years — a number that exceeds the age of the universe.
Neven called the Willow chip is a major step toward commercially relevant quantum computing applications, a goal he and his team have pursued since he founded Google Quantum AI in 2012.
The Google Quantum AI team made a similar announcement in 2019 when Google’s Sycamore quantum system passed the RCS benchmark. Google reported that scientists used the chip to resolve a problem that would have taken a classical supercomputer 10,000 years to calculate.
“The vision was to build a useful, large-scale quantum computer that could harness quantum mechanics — the ‘operating system’ of nature to the extent we know it today — to benefit society by advancing scientific discovery, developing helpful applications, and tackling some of society’s greatest challenges,” Neven said.
Error Correction
Errors are one of the greatest challenges in quantum computing, since qubits, the units of computation in quantum computers, have a tendency to rapidly exchange information with their environment, making it difficult to protect the information needed to complete a computation, reported Neven. Typically the more qubits you use, the more errors will occur, and the system becomes classical.
Yesterday in Nature, the Google Quantum AI team published results showing that the more qubits used in Willow, the more errors were reduced, and the more quantum the system becomes.
“We tested ever-larger arrays of physical qubits, scaling up from a grid of 3×3 encoded qubits, to a grid of 5×5, to a grid of 7×7 — and each time, using our latest advances in quantum error correction, we were able to cut the error rate in half,” Neven said. “In other words, we achieved an exponential reduction in the error rate. This historic accomplishment is known in the field as ‘below threshold’ — being able to drive errors down while scaling up the number of qubits. You must demonstrate being below threshold to show real progress on error correction, and this has been an outstanding challenge since quantum error correction was introduced by Peter Shor in 1995.”
Neven said other scientific “firsts” are involved in this result as well. It’s also one of the first compelling examples of real-time error correction on a superconducting quantum system — crucial for any useful computation, because if you can’t correct errors fast enough, they ruin your computation before it’s done, he explained.
And it’s a “beyond breakeven” demonstration, where Willow’s arrays of qubits have longer lifetimes than the individual physical qubits do, “an unfakable sign that error correction is improving the system overall,” he said.
The result: Willow is the most convincing prototype for a scalable logical qubit built to date, according to Neven.
“It’s a strong sign that useful, very large quantum computers can indeed be built. Willow brings us closer to running practical, commercially-relevant algorithms that can’t be replicated on conventional computers.”
Performance
To measure Willow’s performance, the Google team used the random circuit sampling (RCS) benchmark, which Neven said was pioneered by his team and is now widely used as a standard in the field. He said RCS is the classically hardest benchmark that can be done on a quantum computer today.
“It can be thought of as an entry point for quantum computing — it checks whether a quantum computer is doing something that couldn’t be done on a classical computer,” said Neven. “Any team building a quantum computer should check first if it can beat classical computers on RCS; otherwise there is strong reason for skepticism that it can tackle more complex quantum tasks. We’ve consistently used this benchmark to assess progress from one generation of chip to the next — we reported Sycamore results in October 2019 and again recently in October 2024.”
He said Willow performed a computation in under five minutes that would take one of today’s fastest supercomputers, such as the Frontier exascale system at Oak Ridge National Laboratory, 1025 or 10 septillion years, or 10,000,000,000,000,000,000,000,000 years.
Google quantum performance: the company said considering that computational costs areinfluenced by available memory, their estimates consider a range of scenarios, from an ideal situation with unlimited memory (▲) to a more practical, embarrassingly parallelizable implementation on GPUs (⬤).
Neven said his team’s assessment of how Willow outpaces Frontier was “based on conservative assumptions.” “For example, we assumed full access to secondary storage, i.e., hard drives, without any bandwidth overhead — a generous and unrealistic allowance for Frontier. Of course, as happened after we announced the first beyond-classical computation in 2019, we expect classical computers to keep improving on this benchmark, but the rapidly growing gap shows that quantum processors are peeling away at a double exponential rate and will continue to vastly outperform classical computers as we scale up.”
Willow was fabricated in Google’s new fabrication facility in Santa Barbara — one of only a few facilities in the world built from the ground up for this purpose, according to the company.
“System engineering is key when designing and fabricating quantum chips: All components of a chip, such as single and two-qubit gates, qubit reset, and readout, have to be simultaneously well engineered and integrated,” Neven said. “If any component lags or if two components don’t function well together, it drags down system performance. Therefore, maximizing system performance informs all aspects of our process, from chip architecture and fabrication to gate development and calibration. The achievements we report assess quantum computing systems holistically, not just one factor at a time.”
Neven said that with 105 qubits, Willow “now has best-in-class performance across the two system benchmarks discussed above: quantum error correction and random circuit sampling.”
Florian Neukart, PhD, former head of the quantum program at Volkswagen before joining Terra Quantum, commented: “Google’s achievement in quantum error correction is a significant milestone toward practical quantum computing. It addresses one of the largest hurdles: maintaining coherence and reducing errors during computation. The Willow quantum chip showcases advancements in hardware engineering, with scalable designs focused on fault-tolerant systems.”
Next for Willow
Neven said Google Quantum AI is hopeful about attaining the goal of delivering pratical, useful quantum computation.
“We’re optimistic that the Willow generation of chips can help us achieve this goal,” he said. “So far, there have been two separate types of experiments. On the one hand, we’ve run the RCS benchmark, which measures performance against classical computers but has no known real-world applications. On the other hand, we’ve done scientifically interesting simulations of quantum systems, which have led to new scientific discoveries but are still within the reach of classical computers. Our goal is to do both at the same time — to step into the realm of algorithms that are beyond the reach of classical computers and that are useful for real-world, commercially relevant problems.”
Neven said Google invites researchers, engineers, and developers to join them by checking out their open source software and educational resources, including our new course on Coursera, where developers can learn the essentials of quantum error correction and help us create algorithms that can solve the problems of the future.
