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China’s new quantum computer hits stability milestone, beating Google on efficiency

Chinese team is first outside the US to cross key threshold that determines whether practical quantum computers can work reliably at scale

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Researchers at the University of Science and Technology of China, in the central province of Anhui, stand in front of the Zuchongzhi 3.2 superconducting quantum computing system. Photo:  Handout
Ling Xinin Ohio
Chinese researchers have taken a major step in the global race to build practical quantum computers, becoming the first team outside the United States – and the second in the world after Google – to cross a key threshold that determines whether these machines can work reliably at scale.
A team led by Pan Jianwei at the University of Science and Technology of China said their superconducting quantum computer, Zuchongzhi 3.2, had reached the fault-tolerant threshold – a point where fixing errors made the system more stable rather than less, overcoming a long-standing problem in which the very process of error correction introduces new mistakes.

Their research, published last week in the journal Physical Review Letters, relied on microwave-based control rather than the hardware-intensive error-suppression methods used by Google. The Chinese approach “could offer a more efficient route than Google’s” to building large, fault-tolerant quantum computers, the team said in a statement on Monday.

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Joseph Emerson, a physicist at the University of Waterloo in Canada who was not involved in the research, said the study tackled one of quantum computing’s most difficult problems: qubits drifting out of their intended states and quietly spreading errors through the system.

Writing in the American Physical Society’s Physics magazine, Emerson described the experiment as “an impressive feat”, while cautioning that it remained far from the scale needed for practical, real-world applications.

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Quantum computers work by harnessing the laws of quantum physics rather than the simple on-off logic used by ordinary computers. In theory, this allows them to tackle certain tasks – such as optimising complex systems or simulating molecules – in minutes that would take today’s machines thousands of years to complete.

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