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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

Boson sampling stands out as a promising approach toward experimental demonstration of quantum computational advantage. However, the presence of physical noise in near-term experiments hinders the realization of the quantum computational…

Quantum Physics · Physics 2025-09-30 Byeongseon Go , Changhun Oh , Hyunseok Jeong

Quantum advantage, benchmarking the computational power of quantum machines outperforming all classical computers in a specific task, represents a crucial milestone in developing quantum computers and has been driving different physical…

There is a large body of evidence for the potential of greater computational power using information carriers that are quantum mechanical over those governed by the laws of classical mechanics. But the question of the exact nature of the…

Quantum Physics · Physics 2017-08-23 A. P. Lund , Michael J. Bremner , T. C. Ralph

The problem of sampling outputs of quantum circuits has been proposed as a candidate for demonstrating a quantum computational advantage (sometimes referred to as quantum "supremacy"). In this work, we investigate whether quantum advantage…

Quantum Physics · Physics 2021-06-09 Leonardo Novo , Juani Bermejo-Vega , Raúl García-Patrón

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

Energy consumption in solving computational problems has been gaining growing attention as one of the key performance measures for computers. Quantum computation is known to offer advantages over classical computation in terms of various…

Quantum Physics · Physics 2025-05-23 Florian Meier , Hayata Yamasaki

Machine learning is widely applied in modern society, but has yet to capitalise on the unique benefits offered by quantum resources. Boson sampling -- a quantum-interference based sampling protocol -- is a resource that is classically hard…

Quantum computers promise to dramatically outperform their classical counterparts. However, the non-classical resources enabling such computational advantages are challenging to pinpoint, as it is not a single resource but the subtle…

Quantum Physics · Physics 2023-04-05 Ulysse Chabaud , Mattia Walschaers

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…

Boson sampling, a computational problem conjectured to be hard to simulate on a classical machine, is a promising candidate for an experimental demonstration of quantum advantage using bosons. However, inevitable experimental noise and…

Quantum Physics · Physics 2022-10-12 Gabriele Bressanini , Hyukjoon Kwon , M. S. Kim

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

Giving a convincing experimental evidence of the quantum supremacy over classical simulations is a challenging goal. Noise is considered to be the main problem in such a demonstration, hence it is urgent to understand the effect of noise.…

Quantum Physics · Physics 2022-03-08 Valery Shchesnovich

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 2018-04-10 Bogdan Opanchuk , Laura Rosales-Zarate , Margaret D Reid , Peter D Drummond

Demonstration of quantum advantage for classical machine learning tasks remains a central goal for quantum technologies and artificial intelligence. Two major bottlenecks to this goal are the high dimensionality of practical datasets and…

Quantum Physics · Physics 2025-10-16 Mohammad Sharifian , Abolfazl Bayat

Quantum computer, harnessing quantum superposition to boost a parallel computational power, promises to outperform its classical counterparts and offer an exponentially increased scaling. The term "quantum advantage" was proposed to mark…

The continuous variable quantum computing platform constitutes a promising candidate for realizing quantum advantage, as exemplified in Gaussian Boson Sampling. While noise in the experiments makes the computation attainable for classical…

Quantum Physics · Physics 2025-08-11 Jonas Vinther , Michael James Kastoryano

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

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 computing promises the ability to compute properties of quantum systems exponentially faster than classical computers. Quantum advantage is achieved when a practical problem is solved more efficiently on a quantum computer than on a…

Quantum Physics · Physics 2025-12-03 William A. Simon , Peter J. Love
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