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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) is a prominent candidate for the experimental demonstration of quantum advantage. However, while the current implementations of GBS are unavoidably subject to noise, the robustness of the classical…

Quantum Physics · Physics 2025-11-12 Byeongseon Go , Changhun Oh , Hyunseok Jeong

Gaussian boson sampling is a promising candidate for showing experimental quantum advantage. While there is evidence that noiseless Gaussian boson sampling is hard to efficiently simulate using a classical computer, the current Gaussian…

Quantum Physics · Physics 2024-09-24 Changhun Oh , Minzhao Liu , Yuri Alexeev , Bill Fefferman , Liang Jiang

Gaussian boson sampling (GBS) is considered a candidate problem for demonstrating quantum advantage. We propose an algorithm for approximate classical simulation of a lossy GBS instance. The algorithm relies on the Taylor series expansion,…

Quantum Physics · Physics 2024-04-02 M. V. Umanskii , A. N. Rubtsov

Gaussian boson sampling (GBS) allows for a way to demonstrate quantum supremacy with the relatively modest experimental resources of squeezed light sources, linear optics, and photon detection. In a realistic experimental setting, numerous…

Quantum Physics · Physics 2022-03-09 Junheng Shi , Tim Byrnes

Identifying the boundary beyond which quantum machines provide a computational advantage over their classical counterparts is a crucial step in charting their usefulness. Gaussian Boson Sampling (GBS), in which photons are measured from a…

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 is a model of photonic quantum computing that has attracted attention as a platform for building quantum devices capable of performing tasks that are out of reach for classical devices. There is therefore significant…

Gaussian boson sampling is a promising model for demonstrating quantum computational supremacy, which eases the experimental challenge of the standard boson-sampling proposal. Here by analyzing the computational costs of classical…

Quantum Physics · Physics 2019-08-28 Bujiao Wu , Bin Cheng , Jialin Zhang , Man-Hong Yung , Xiaoming Sun

Quantum mechanics promises computational powers beyond the reach of classical computers. Current technology is on the brink of an experimental demonstration of the superior power of quantum computation compared to classical devices. For…

Quantum Physics · Physics 2019-04-02 Jelmer Renema , Valery Shchesnovich , Raul Garcia-Patron

Gaussian boson sampling (GBS) is not only a feasible protocol for demonstrating quantum computational advantage, but also mathematically associated with certain graph-related and quantum chemistry problems. In particular, it is proposed…

The tantalizing promise of quantum computational speedup in solving certain problems has been strongly supported by recent experimental evidence from a high-fidelity 53-qubit superconducting processor1 and Gaussian boson sampling (GBS) with…

A growing cohort of experimental linear photonic networks implementing Gaussian boson sampling (GBS) have now claimed quantum advantage. However, many open questions remain on how to effectively verify these experimental results, as…

Quantum Physics · Physics 2023-08-03 Alexander S. Dellios , Margaret D. Reid , Peter D. Drummond

Boson sampling, a computational task believed to be classically hard to simulate, is expected to hold promise for demonstrating quantum computational advantage using near-term quantum devices. However, noise in experimental implementations…

Quantum Physics · Physics 2026-03-17 Byeongseon Go , Changhun Oh , Hyunseok Jeong

Quantum computers solve intractable problems which classically require an exponentially long time to compute. With the development of large-scale experiments that claim quantum advantage, a vital issue has now emerged. What are the errors,…

Quantum Physics · Physics 2026-04-15 Ned Goodman , Alexander S. Dellios , Margaret D. Reid , Peter D. Drummond

Gaussian boson sampling (GBS) is a model of nonuniversal quantum computation that claims to demonstrate quantum supremacy with current technologies. This model entails sampling photocounting events from a multimode Gaussian state at the…

Quantum Physics · Physics 2024-10-22 I. S. Yeremenko , M. A. Dmytruk , A. A. Semenov

Gaussian Boson sampling (GBS) provides a highly efficient approach to make use of squeezed states from parametric down-conversion to solve a classically hard-to-solve sampling problem. The GBS protocol not only significantly enhances the…

We introduce an exact classical algorithm for simulating Gaussian Boson Sampling (GBS). The complexity of the algorithm is exponential in the number of photons detected, which is itself a random variable. For a fixed number of modes, the…

Quantum Physics · Physics 2020-11-18 Nicolás Quesada , Juan Miguel Arrazola

Gaussian Boson Sampling is a model of photonic quantum computing where single-mode squeezed states are sent through linear-optical interferometers and measured using single-photon detectors. In this work, we employ a recent exact sampling…

Quantum Physics · Physics 2021-03-29 Brajesh Gupt , Juan Miguel Arrazola , Nicolás Quesada , Thomas R. Bromley

We present a classical algorithm that approximately samples from the output distribution of certain noisy Boson Sampling experiments. This algorithm is inspired by a recent result of Aharonov, Gao, Landau, Liu and Vazirani and makes use of…

Quantum Physics · Physics 2023-01-30 Changhun Oh , Liang Jiang , Bill Fefferman
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