[Music] Introducing our latest quantum computing chip, developed to learn and evolve like the natural world around us: Willow, from Google Quantum AI. [Music] Hi, I'm Julian Kelly, director of hardware at Google Quantum AI, and today, on behalf of our amazing team, I'm proud

to announce Willow. Willow is Google's newest and most powerful superconducting quantum computing chip and the next step in our path towards building large-scale quantum computers and exploring their applications. I have been fascinated with quantum computing since I first experimented with qubits in 2008, and

since coming to Google in 2015, it has been a dream to make our mission our reality: building quantum computers for otherwise unsolvable problems. We launched our first chip, Foxtail, in 2017, followed by Bristlecone in 2018 and Sycamore in 2019, which

powered our Milestone one: the first quantum computer to surpass the best classical supercomputer on a computational task—random circuit sampling. Over the years with Sycamore, we have been able to squeeze a remarkable amount of performance from our hardware, including achieving a scalable logical

qubit in our Milestone two. But we've ultimately been limited by quantum coherence times—the length of time qubits maintain their intended state. With Willow, we've made a huge step forward. We've increased quantum coherence times by a factor of five, going from 20 microseconds

in Sycamore to 100 microseconds in Willow. And we've accomplished this all without sacrificing any of the features that made our systems so successful. This advancement was enabled by our new dedicated superconducting quantum chip fabrication facility in Santa Barbara, one of only a few in the

World, and we're seeing exciting developments coming from Willow, which has already surpassed Sycamore's breakthrough demonstrations. Our logical qubits now operate below the critical quantum error correction threshold, a long sought-after goal for the quantum computing field.

Since the theory was discovered in the 90s, and we've achieved it for the first time with Willow. Errors are exponentially suppressed in our logical qubits as error rates are halved each time we add physical qubits in scale from distance 3 to 5 to 7 surface codes.

Additionally, our logical qubit lifetimes are now much longer than all of the lifetimes of the physical qubits that compose them. This means that even as we make our quantum chips larger and more complex by adding more qubits, we can use quantum error correction to actually

improve their accuracy. We've pitted Willow against one of the world's most powerful supercomputers with the random circuit sampling benchmark. The results are pretty surprising. By our best estimates, a calculation that takes Willow under five minutes would take the

fastest supercomputer 10 to the 25th years—that's 10 with 25 zeros following it—or a time scale way longer than the age of the universe. This result highlights the exponentially growing gap between classical and quantum computation for

certain applications. Let's talk about the hardware approach we've pioneered at Google Quantum AI that makes these things possible. Our tunable circuits and couplers enable super-fast gates and operations to achieve low error rates, reconfigurability to optimize hardware in situ, and run

Multiple applications and high connectivity efficiently express algorithms. We leverage this tunability to enable reproducible, high performance across the device. Let me explain a challenge in superconducting cubits: not all of them are created equal. Some are outliers with

uncharacteristically high errors. But here's where our TRIN cubits really shine. We're able to fix these outlier cubits by reconfiguring them to perform in line with the rest of the device. And we can go one step further by having our

researchers use tunability to continuously develop new calibration strategies that push errors down across all key bits with software. Let's quantify this and nerd out for a minute on quantum computer tech specs. We have: number of cubits; connectivity (the average number of

interactions each qubit can perform with its neighbors); we quantify error probabilities for running simultaneous operations: single-qubit gates, two-qubit gates, and measurement; coherence time (measures how long each qubit can retain its information); measurement rate (how many computations we can run per second).

Application performance is a full-system benchmark. Willow hits a sweet spot across the full list. It has a large number of qubits with high connectivity and can run diverse applications. We measure low mean error rates across all operations with multiple native two-qubit gates. We have greatly increased T1 times,

we have very high measurement rates, and Willow is below the error correction threshold and performs random circuit sampling far beyond what is possible with classical computers. Looking to the future with Willow, we continue our journey towards building large-scale and useful, error-corrected quantum computers that will

Push the boundaries of science and the exploration of nature, with future commercially useful applications in areas like pharmaceuticals, batteries, and fusion power. We are excited to solve the otherwise unsolvable problems of tomorrow.

Google Quantum AI Reveals Willow Quantum Computing Chip

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Google Quantum AI Reveals Willow Quantum Computing Chip

Google Quantum AI Reveals Willow Quantum Computing Chip

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