As one of the major players in quantum computing, Google Quantum AI took a big step recently that’s worth celebrating. They proposed a new quantum algorithm that shows incredible progress compared to any classical computing approaches. The team reports that this algorithm can execute tasks approximately 13,000 times faster than its best classical counterpart running on the Frontier supercomputer. This implementation comes amidst an ongoing discussion regarding the tangible benefits of quantum computing. The most common criticism is the focus on nonsensical tasks to demonstrate quantum superiority.
The new algorithm takes a different approach from previous ones, using the entire quantum computer to apply a small perturbation to a qubit. This tiny tweak makes a huge difference over long-range qubits. It’s sort of like the butterfly effect in that even small differences can result in big changes. Such capabilities aptly underscore the promise for this algorithm to augment computational power in manners only before unimagined with classical systems.
Achieving Verifiable Quantum Advantage
In a pair of recent demonstrations, two quantum processors ran the new algorithm in parallel, each successfully producing identical results. This is what the experts call verifiable quantum advantage. This success lays the groundwork on Google’s previous success in 2019, when they first showed quantum advantage through random circuit sampling. In that experiment, only 0.1 percent of the collected data had to be accurate. With the new algorithm, 0.1 percent of the data is allowed to be incorrect.
Hartmut Neven, co-founder and managing director of Google Quantum AI, said he was hopeful about the implications of this breakthrough. He noted, “We continue to be optimistic that within five years, we will see real-world applications that are only possible with quantum computers.” Even industry would agree that quantum computing is on the verge of leaping from theory to practical application. This sentiment underscores the increasing confidence in the development of practical applications.
Impacts on Molecular Simulations
Perhaps the biggest challenge conventional supercomputers have yet to overcome is accurately simulating molecular interactions. Google’s Sycamore quantum computer famously did a particular, complex calculation in just 200 seconds using 54 qubits. By contrast, Summit, the world’s most powerful supercomputer back then, would have taken an impressive—but still impractical—10,000 years to complete the same job. The newest Willow chip has a whopping 105 qubits. It upended the field of computation by doing complicated benchmark tasks in under five minutes—tasks that Frontier would take a mind-numbing 10 septillion years to accomplish.
Willow’s architecture will be critical, according to Michel Devoret, chief scientist of quantum hardware at Google Quantum AI. Willow’s also known for a huge number of qubits, with an overall error rate of 0.1 percent. This makes it perfectly camouflaged to satisfy the new algorithm’s demands. This combination has allowed researchers to generate accurate and precise models of molecular structures using experiments involving up to 15 of Willow’s qubits.
“If I can’t prove to you that the data is correct, how can I do anything with it?” – Thomas O’Brien
The newly developed algorithm adds a different level of complexity to molecular modeling. For example, an algorithm may show a new finding when you perturb a particular qubit during calculations. We need to look at the different pieces that make up this molecule. Thomas O’Brien, a staff research scientist at Google Quantum AI, elaborated on the significance of verification in this context, stating, “The key aspect of verification is that it can lead to applications.”
Future Applications and Industry Expectations
With Google Quantum AI’s ongoing development of their quantum algorithms, anticipation about their potential use in real-world situations increases. These computational feats are a testament to the rapid advances we have made. They show the promise for truly transformative impacts, particularly in areas such as materials science, pharmaceuticals and simulations of complex systems.
Given this history of critics dismissing many of these quantum advantage claims for being based on trivial or impractical tasks, this recent advance might go a long way to shifting those perceptions, because it’s showing us what’s possible with true computational breakthroughs rooted in serious scientific research.
The race to find practical applications for quantum computing is heating up. Each one—like this week’s new algorithm from Google Quantum AI—takes us a step closer to realizing the potential of quantum mechanics to deliver transformative real-world benefits. Researchers are continuing to push the frontiers of this promising technology. Capabilities that are soon to come will reshape what we know as computation.
