In 2019, Google claimed that its Sycamore quantum computer could perform calculations that would take even the world鈥檚 most powerful classical supercomputer 10,000 years to complete 鈥� but now it seems that a non-quantum computer crunches the numbers several times faster than Google鈥檚 machine, and uses less energy doing so.
Quantum computers have the potential to carry out some kinds of calculations vastly more quickly than classical computers, but are still in their infancy. Google announced in 2019 that Sycamore had achieved 聽鈥渜uantum supremacy鈥� 鈥� the point at which a quantum computer can complete a task that would be, for all intents and purposes, impossible for ordinary computers.
The task involved verifying that a sample of numbers output by a quantum circuit have a truly random distribution, which Sycamore was able to complete in 3 minutes and 20 seconds. The Google team said that even the world鈥檚 most powerful supercomputer at the time, IBM鈥檚 Summit, would take 10,000 years to achieve the same result.
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But since then, classical computers 鈥� the non-quantum kind 鈥� have closed the gap. In 2022, researchers used 512 graphics processing units (GPUs) to complete the task in around 15 hours, and now Rong Fu at the Shanghai Artificial Intelligence Laboratory in China and her colleagues have completed the same task in 14.22 seconds.
The researchers needed some beefy hardware to set this record. They used a computer featuring more than 2300 Nvidia A100 GPUs, which is one of the most advanced classical computer chips in existence and retails for tens of thousands of dollars each. What鈥檚 more, the device consumed less energy than Sycamore, at 2.39 kilowatt hours (kWh) versus Google鈥檚 4.3 kWh.
To explore the trade-off between energy consumption and speed, the researchers also performed the computation in just over 17 seconds with energy consumption of only 0.29 kWh, leading them to declare both computational superiority and 鈥渆nergy superiority鈥� over Google鈥檚 quantum computer.
Google wasn鈥檛 able to provide a comment on the new work before publication, but in 2022 , principal scientist at Google Quantum AI, responded to the previous classical advance: 鈥淚n our 2019 paper we said that classical algorithms would improve鈥� but the key point is that quantum technology improves exponentially faster. So we don鈥檛 think this classical approach can keep up with quantum circuits in 2022 and beyond, despite significant improvements in the last few years.鈥�
鈥淭he 2019 paper stands in that it was a supremacy result based on known classical methods at the time,鈥� says at quantum computer start-up Orca Computing. He thinks that the arms race between quantum and classical machines is valuable to spur innovation, but that, as the field matures, each claim of supremacy and counter-claim against it will be less meaningful. 鈥淚t鈥檚 important for quantum technology to establish capabilities that justify the investment. On the other hand, it鈥檚 important that those claims are scrutinised,鈥� he says.
鈥淚t鈥檚 no surprise that there are esoteric cases where a programmable quantum system can solve some problem that we cannot solve using regular computers,鈥� he says. 鈥淏ut for valuable quantum computing, all that鈥檚 needed is a user base that demands to use quantum computers for some application 鈥� even if it鈥檚 possible to do it using regular computers.鈥�
arXiv
