Led by the renowned Chinese quantum physicist Pan Jianwei, the research team has successfully accomplished this quantum computing feat, achieving a speed that is 10 quadrillion times faster in solving Gaussian boson sampling (GBS) problems compared to the world's existing fastest supercomputers.
Gaussian boson sampling, a classically intractable problem, was employed in this study to provide a highly efficient way of demonstrating quantum computational speedup in solving some well-defined tasks.
The study was published online in the journal Physical Review Letters on Wednesday Beijing Time.
Lu Chaoyang, a member of the research team and professor at the University of Science and Technology of China, said that a series of innovations, including a newly developed superconducting nanowire single-photon detection scheme with fiber loop-based configuration, increased the number of detected photons for "Jiuzhang 3.0" to 255, greatly improving the complexity of photonics quantum computing.
"By demultiplexing photons into time bins through delays, we've achieved capabilities of pseudo photon number resolving," Lu added.
According to the state-of-the-art exact classical simulation algorithm, "Jiuzhang 3.0" is a million times faster at solving GBS problems than its predecessor, "Jiuzhang 2.0." Moreover, the most complex samples of GBS that "Jiuzhang 3.0" can calculate in just one microsecond would take the world's fastest supercomputer, "Frontier," more than 20 billion years to complete.
In 2021, the team led by Pan developed the "Jiuzhang 2.0" with 113 detected photons and a 66-qubit programmable superconducting quantum computing system named "Zuchongzhi 2.1," making China the only country to achieve a quantum computational advantage in two mainstream technical routes -- one via photonics quantum computing technology and the other via superconducting quantum computing technology.
Establishing quantum computational advantage requires great endeavor, with long-term competition between classical algorithms and quantum computing hardware, the team noted. They anticipate that this work will, on one hand, stimulate more research on classical simulation algorithms, and on the other hand, through diligent efforts, gradually address various scientific and engineering challenges in quantum computing research. Ultimately, quantum computers will achieve computational power beyond the reach of classical computers, driving the advancement of science and technology.
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