China Challenges Google’s Quantum Breakthrough
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The method of simulating quantum computations by Chinese scientists can re-perform Google’s test in 5 days.
The field of quantum computing is still in its infancy, but promises to elevate the computing power of humans to a new level by controlling subatomic particles. Scientists hope it will be the foundation for breakthroughs in fields such as new drug-making and materials science.
This is also one of the Chinese government’s top development priorities. Last week, the country adopted its 14th five-year development plan, focusing on key science and technology industries, especially applications such as ultra-secure communication networks and precise measurement.
“Quantum advantage” is a developmental milestone, marking the difference in computational power between quantum machines and classical computers.
In October 2019, Google announced its Sycamore processor was the first quantum computer to achieve quantum advantage by solving a task in 3 minutes and 20 seconds, which is the world’s most powerful supercomputer IBM Summit. it took 10,000 years to complete.
Sycamore’s claims of strength and especially the 10,000-year number that Google scientists gave were doubted by many researchers. They argue that, in theory, by changing some of the algorithms and configurations, similar task-processing times of a classic supercomputer could be reduced to just a few days —not too far from what Google’s Sycamore achieves.
In Beijing, researchers at the Institute of Theoretical Physics at the Chinese Academy of Sciences demonstrated this hypothesis by repeating Google’s test but using the computing power of 60 Nvidia V100 graphics processors and A100, which is often used for artificial intelligence tasks.
The scientists said they completed this task “in about 5 days”. Impressive results are achieved using a new simulation algorithm based on the general tensor lattice method. This algorithm “cuts” the tasks into small samples that are optimal for classical processors of computing. This method gives much higher accuracy than samples from…
