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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…

Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based problems, point processes, and molecular vibronic spectra in…

Gaussian boson sampling (GBS) is a promising candidate for an experimental demonstration of quantum advantage using photons. However, sufficiently large noise might hinder a GBS implementation from entering the regime where quantum speedup…

Quantum Physics · Physics 2024-01-24 Gabriele Bressanini , Hyukjoon Kwon , M. S. Kim

Gaussian Boson Sampling (GBS) generate random samples of photon-click patterns from a class of probability distributions that are hard for a classical computer to sample from. Despite heroic demonstrations for quantum supremacy using GBS,…

Quantum Physics · Physics 2024-02-07 Mushkan Sureka , Saikat Guha

Gaussian Boson Sampling (GBS) exhibits a unique ability to solve graph problems, such as finding cliques in complex graphs. It is noteworthy that many drug discovery tasks can be viewed as the clique-finding process, making them potentially…

Gaussian Boson Sampling (GBS) is a recently developed paradigm of quantum computing consisting of sending a Gaussian state through a linear interferometer and then counting the number of photons in each output mode. When the system encodes…

Gaussian Boson Sampling (GBS) is a quantum computational model that leverages linear optics to solve sampling problems believed to be classically intractable. Recent experimental breakthroughs have demonstrated quantum advantage using GBS,…

Quantum Physics · Physics 2026-01-29 Jesua Epequin , Pascale Bendotti , Joseph Mikael

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

Recently, Zhong et al. performed landmark Gaussian boson sampling experiments with up to 144 modes using threshold detectors. The authors claim to have achieved quantum computational advantage with the implementation of these experiments,…

Quantum Physics · Physics 2023-08-09 Javier Martínez-Cifuentes , K. M. Fonseca-Romero , Nicolás Quesada

Scientists in quantum technology aspire to quantum advantage: a computational result unattainable with classical computers. Gaussian boson sampling experiment has been already claimed to achieve this goal. In this setup squeezed light…

Quantum Physics · Physics 2022-07-08 A. S. Popova , A. N. Rubtsov

Boson Sampling is a computational task strongly believed to be hard for classical computers, but efficiently solvable by orchestrated bosonic interference in a specialised quantum computer. Current experimental schemes, however, are still…

Boson sampling is expected to be one of an important milestones that will demonstrate quantum supremacy. The present work establishes the benchmarking of Gaussian boson sampling (GBS) with threshold detection based on the Sunway TaihuLight…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-03 Yuxuan Li , Mingcheng Chen , Yaojian Chen , Haitian Lu , Lin Gan , Chaoyang Lu , Jianwei Pan , Haohuan Fu , Guangwen Yang

Gaussian boson sampling is originally proposed to show quantum advantage with quantum linear optical elements. Recently, several experimental breakthroughs based on Gaussian boson sampling pointing to quantum computing supremacy have been…

Quantum Physics · Physics 2023-01-02 Tian-Yu Yang , Yi-Xin Shen , Zhou-Kai Cao , Xiang-Bin Wang

A universal quantum computer of large scale is not available yet, however, intermediate models of quantum computation would still permit demonstrations of a quantum computational advantage over classical computing and could challenge the…

Quantum Physics · Physics 2024-11-15 Raphael A. Abrahao , Arman Mansouri , Austin P. Lund

If classical algorithms have been successful in reproducing the estimation of expectation values of observables of some quantum circuits using off-the-shelf computing resources, matching the performance of the most advanced quantum devices…

Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage towards the realization of universal quantum computers. In the context of non-universal noisy intermediate…

Quantum Physics · Physics 2025-01-14 Denis Stanev , Taira Giordani , Nicolò Spagnolo , Fabio Sciarrino

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

Gaussian boson sampling (GBS), a computational problem conjectured to be hard to simulate on a classical machine, has been at the forefront of recent years' experimental and theoretical efforts to demonstrate quantum advantage. The…

Quantum Physics · Physics 2024-02-05 Gabriele Bressanini , Benoit Seron , Leonardo Novo , Nicolas J. Cerf , M. S. Kim

Boson Sampling has emerged as a tool to explore the advantages of quantum over classical computers as it does not require a universal control over the quantum system, which favours current photonic experimental platforms.Here, we introduce…

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