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A Gaussian boson sampler (GBS) is a special-purpose quantum computer that can be practically realized at large scale in optics. Here we report on experiments in which we used a frequency-multiplexed GBS with $>400$ modes as the reservoir in…

The demonstration of quantum speedup, also known as quantum computational supremacy, that is the ability of quantum computers to outperform dramatically their classical counterparts, is an important milestone in the field of quantum…

Quantum Physics · Physics 2021-11-17 Ulysse Chabaud , Frédéric Grosshans , Elham Kashefi , Damian Markham

Gaussian boson sampling (GBS) is quantum sampling task in which one has to draw samples from the photon-number distribution of a large-dimensional nonclassical squeezed state of light. In an effort to make this task intractable for a…

Quantum Physics · Physics 2022-05-25 G. S. Thekkadath , S. Sempere-Llagostera , B. A. Bell , R. B. Patel , M. S. Kim , I. A. Walmsley

Gaussian boson sampling (GBS) is a variety of boson sampling overcoming the stable single-photon preparation difficulty of the later. However, like those in the original version, noises in GBS will also result in the deviation of output…

Quantum Physics · Physics 2026-05-19 Yang Ji , Yongzheng Wu , Shi Wang , Jie Hou , Zijian Wang , Bo Jiang

Gaussian Boson Sampling (GBS) have shown advantages over classical methods for performing some specific sampling tasks. To fully harness the computational power of GBS, there has been great interest in identifying their practical…

Quantum Physics · Physics 2025-02-28 Jørgen Ellegaard Andersen , Shan Shan

BosonSampling is an intermediate model of quantum computation where linear-optical networks are used to solve sampling problems expected to be hard for classical computers. Since these devices are not expected to be universal for quantum…

Quantum Physics · Physics 2016-01-27 Scott Aaronson , Daniel J. Brod

Random quantum circuit sampling serves as a benchmark to demonstrate quantum computational advantage. Recent progress in classical algorithms, especially those based on tensor network methods, has significantly reduced the classical…

Validation of quantum advantage claims in the context of Gaussian Boson Sampling (GBS) currently relies on providing evidence that the experimental samples genuinely follow their corresponding ground truth, i.e., the theoretical model of…

Quantum Physics · Physics 2024-10-03 Javier Martínez-Cifuentes , Hubert de Guise , Nicolás Quesada

Gaussian boson sampling constitutes a prime candidate for an experimental demonstration of quantum advantage within reach with current technological capabilities. The original proposal employs photon-number-resolving detectors, however the…

Quantum Physics · Physics 2024-02-14 Gabriele Bressanini , Hyukjoon Kwon , M. S. Kim

We show how phase-space simulations of Gaussian quantum states in a photonic network permit verification of measurable correlations of Gaussian boson sampling (GBS) quantum computers. Our results agree with experiments for up to 100-th…

Quantum Physics · Physics 2022-02-09 Peter D. Drummond , Bogdan Opanchuk , Alexander Dellios , Margaret D. Reid

Multiphoton interference is at the very heart of quantum foundations and applications in quantum sensing and information processing. In particular, boson sampling experiments have the potential to demonstrate quantum computational supremacy…

Quantum Physics · Physics 2021-09-15 Vincenzo Tamma , Simon Laibacher

Gaussian boson sampling, a computational model that is widely believed to admit quantum supremacy, has already been experimentally demonstrated and is claimed to surpass the classical simulation capabilities of even the most powerful…

Quantum Physics · Physics 2023-11-17 Minzhao Liu , Changhun Oh , Junyu Liu , Liang Jiang , Yuri Alexeev

Boson Sampling is the problem of sampling from the same distribution as indistinguishable single photons at the output of a linear optical interferometer. It is an example of a non-universal quantum computation which is believed to be…

Quantum Physics · Physics 2019-11-28 Alexandra E. Moylett , Raúl García-Patrón , Jelmer J. Renema , Peter S. Turner

The search for new, application-specific quantum computers designed to outperform any classical computer is driven by the ending of Moore's law and the quantum advantages potentially obtainable. Photonic networks are promising examples,…

Quantum Physics · Physics 2018-04-13 B. Opanchuk , L. Rosales-Zárate , M. D. Reid , P. D. Drummond

Loop-based boson samplers interfere photons in the time degree of freedom using a sequence of delay lines. Since they require few hardware components while also allowing for long-range entanglement, they are strong candidates for…

Universal quantum computers promise a dramatic speed-up over classical computers but a full-size realization remains challenging. However, intermediate quantum computational models have been proposed that are not universal, but can solve…

Gaussian Boson Sampling is a promising method for experimental demonstrations of quantum advantage because it is easier to implement than other comparable schemes. While most of the properties of Gaussian Boson Sampling are understood to…

Boson sampling is considered as a strong candidate to demonstrate the quantum computational supremacy over classical computers. However, previous proof-of-principle experiments suffered from small photon number and low sampling rates owing…

Boson sampling is a key candidate for demonstrating quantum advantage, and has already yielded significant advances in quantum simulation, machine learning, and graph theory. In this work, a unification and extension of distinct forms of…

Quantum Physics · Physics 2025-12-29 Luca Bianchi , Carlo Marconi , Laura Ares , Davide Bacco , Jan Sperling

We have recently seen the first plausible claims for quantum advantage using sampling problems such as random circuit sampling and Gaussian boson sampling. The obvious next step is to channel the potential quantum advantage to solving…

Quantum Physics · Physics 2024-06-27 Changhun Oh , Youngrong Lim , Yat Wong , Bill Fefferman , Liang Jiang