Today, Nature published its 150th anniversary issue with the news that Google’s team of researchers have achieved a big breakthrough in quantum computing known as quantum supremacy. It’s a term of art that means we’ve used a quantum computer to solve a problem that would take a classical computer an impractically long amount of time. This moment represents a distinct milestone in our effort to harness the principles of quantum mechanics to solve computational problems.
While we’re excited for what’s ahead, we are also very humbled by the journey it took to get here. And we’re mindful of the wisdom left to us by the great Nobel Laureate Richard Feynman: “If you think you understand quantum mechanics, you don't understand quantum mechanics.”
In many ways, the exercise of building a quantum computer is one long lesson in everything we don’t yet understand about the world around us. While the universe operates fundamentally at a quantum level, human beings don’t experience it that way. In fact many principles of quantum mechanics directly contradict our surface level observations about nature. Yet the properties of quantum mechanics hold enormous potential for computing.
A bit in a classical computer can store information as a 0 or 1. A quantum bit—or qubit—can be both 0 and 1 at the same time, a property called superposition. So if you have two quantum bits, there are four possible states that you can put in superposition, and those grow exponentially. With 333 qubits there are 2^333, or 1.7x10^100—a Googol—computational states you can put in superposition, allowing a quantum computer to simultaneously explore a rich space of many possible solutions to a problem.
As we scale up the computational possibilities, we unlock new computations. To demonstrate supremacy, our quantum machine successfully performed a test computation in just 200 seconds that would have taken the best known algorithms in the most powerful supercomputers thousands of years to accomplish. We are able to achieve these enormous speeds only because of the quality of control we have over the qubits. Quantum computers are prone to errors, yet our experiment showed the ability to perform a computation with few enough errors at a large enough scale to outperform a classical computer.
For those of us working in science and technology, it’s the “hello world” moment we’ve been waiting for—the most meaningful milestone to date in the quest to make quantum computing a reality. But we have a long way to go between today’s lab experiments and tomorrow’s practical applications; it will be many years before we can implement a broader set of real-world applications.
We can think about today’s news in the context of building the first rocket that successfully left Earth’s gravity to touch the edge of space. At the time, some asked: Why go into space without getting anywhere useful? But it was a big first for science because it allowed humans to envision a totally different realm of travel … to the moon, to Mars, to galaxies beyond our own. It showed us what was possible and nudged the seemingly impossible into frame.
That’s what this milestone represents for the world of quantum computing: a moment of possibility.
It’s been a 13-year journey for Google to get here. In 2006, Google scientist Hartmut Neven started exploring the idea of how quantum computing might help our efforts to accelerate machine learning. This work led to the founding of our Google AI Quantum team, and in 2014, John Martinis and his team at the University of California at Santa Barbara joined us in our efforts to build a quantum computer. Two years later, Sergio Boixo published a paper that focused our efforts around the well-defined computational task of quantum supremacy, and now the team has built the world’s first quantum system that exceeds the capabilities of supercomputers for this particular computation.
We made these early bets because we believed—and still do—that quantum computing can accelerate solutions for some of the world's most pressing problems, from climate change to disease. Given that nature behaves quantum mechanically, quantum computing gives us the best possible chance of understanding and simulating the natural world at the molecular level. With this breakthrough we’re now one step closer to applying quantum computing to—for example—design more efficient batteries, create fertilizer using less energy, and figure out what molecules might make effective medicines.
Those applications are still many years away and we are committed to building the error-corrected quantum computer that will power these discoveries. We’ve always known that it would be a marathon, not a sprint. The thing about building something that hasn’t been proven yet is that there is no playbook. If the team needed a part, they had to invent it and build it themselves. And if it didn’t work—and often, it didn’t—they had to redesign and build it again.
One turning point came in October 2018, when the wildfires were raging in Southern California. I got a message that they would need to close down the Santa Barbara laboratory for a few days out of an abundance of caution. What I didn’t know was that the team had been experiencing one of those periods where progress had slowed to a crawl. The few days of forced vacation helped the team to reset and think about things differently, and a few months later, they made this breakthrough.
As with any advanced technology, quantum computing raises its own anxieties and questions. In thinking through these issues, we’re following a set of AI principles that we developed to help guide responsible innovation of advanced technology. For example, for many years the security community, with contributions from Google, has been working on post-quantum cryptography, and we’re optimistic we are ahead of the curve when it comes to future encryption concerns. We will continue to publish research and help the broader community develop quantum encryption algorithms using our open source framework Cirq. We’ve appreciated the National Science Foundation’s support for our researchers, and we’ve collaborated with NASA Ames and Oak Ridge National Laboratory on this latest result. As was the case with the Internet and machine learning, government support of basic research remains critical to long-term scientific and technological achievement.
I am excited about what quantum computing means for the future of Google and the world. Part of that optimism comes from the nature of the technology itself. You can trace the progress from the mega-computers of the 1950s to advances we’re making in artificial intelligence today to help people in their everyday lives.
Quantum computing will be a great complement to the work we do (and will continue to do) on classical computers. In many ways quantum brings computing full circle, giving us another way to speak the language of the universe and understand the world and humanity not just in 1s and 0s but in all of its states: beautiful, complex, and with limitless possibility.