Quantum computational advantage using photons

By Han-Sen Zhong, Hui Wang, Yu-Hao Deng, Ming-Cheng Chen, Li-Chao Peng, Yi-Han Luo, J. Qin, Dian Wu, X. Ding, Y. Hu and 14 more. Science, 2020

2,377 citations recorded by the source corpus.

A light approach to quantum advantage Quantum computational advantage or supremacy is a long-anticipated milestone toward practical quantum computers. Recent work claimed to have reached this point, but subsequent work managed to speed up the classical simulation and pointed toward a sample size–dependent loophole. Quantum computational advantage, rather than being a one-shot experimental proof, will be the result of a long-term competition between quantum devices and classical simulation. Zhong et al. sent 50 indistinguishable single-mode squeezed states into a 100-mode ultralow-loss interferometer and sampled the output using 100 high-efficiency single-photon detectors. By obtaining up to 76-photon coincidence, yielding a state space dimension of about 1030, they measured a sampling rate that is about 1014-fold faster than using state-of-the-art classical simulation strategies and supercomputers. Science, this issue p. 1460 Quantum computational advantage is demonstrated using boson sampling with photons. Quantum computers promise to perform certain tasks that are believed to be intractable to classical computers. Boson sampling is such a task and is considered a strong candidate to demonstrate the quantum computational advantage. We performed Gaussian boson sampling by sending 50 indistinguishable single-mode squeezed states into a 100-mode ultralow-loss interferometer with full connectivity and random matrix—the whole optical setup is phase-locked—and sampling the output using 100 high-efficiency single-photon detectors. The obtained samples were validated against plausible hypotheses exploiting thermal states, distinguishable photons, and uniform distribution. The photonic quantum computer, Jiuzhang, generates up to 76 output photon clicks, which yields an output state-space dimension of 1030 and a sampling rate that is faster than using the state-of-the-art simulation strategy and supercomputers by a factor of ~1014.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/d9136c3249aaf5fbe71c6895911391a8dd589d69

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Citations in the corpus

Practical quantum advantage in quantum simulation (2022, background): “…the exploration of out-of-equilibrium dynamics of the Hubbard model 30,31 , disordered, interacting many-particle systems 82 , topological phases of matter 32,33,83 , robust features of out of equilibrium dynamics such as quantum many-body scars 34,84 , and Boson sampling as noted earlier 10 .”
Quantum computational advantage with a programmable photonic processor (2022, methodology): “Our solutions to these challenges for this work are, respectively, (1) the design of a bright and tunable source of single-mode squeezed states and phase stabilization techniques (OPO and interferometer) using locking schemes compatible with PNR detectors, (2) active demultiplexing to increase the e”
Variational quantum algorithms (2020, background): “This size actually allows one to achieve quantum supremacy, outperforming the best classical supercomputer, for certain contrived mathematical tasks [8, 9].”
Quantum Technologies Need a Quantum Energy Initiative (2021, methodology): “A milestone was reached in 2019 with Google’s Sycamore quantum processor made of 53 functional superconducting qubits [4], followed by boson sampling experiments involving a few tens of photons [37].”
Highlighting photonics: looking into the next decade (2021, background): “1 a Artwork illustrating the boson sampling experiment to achieve photonic quantum supremacy, as established in a quantum computer called “Jiuzhang” [30] [Image credit: Yihan Luo/ScienceNews]. b Artwork illustrating the entanglement structure of a large-scale quantum processor made of light, highlig”