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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

Boson-Sampling is a classically computationally hard problem that can - in principle - be efficiently solved with quantum linear optical networks. Very recently, a rush of experimental activity has ignited with the aim of developing such…

Quantum Physics · Physics 2020-05-15 C. Gogolin , M. Kliesch , L. Aolita , J. Eisert

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

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

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

As a promising candidate for exhibiting quantum computational supremacy, Gaussian Boson Sampling (GBS) is designed to exploit the ease of experimental preparation of Gaussian states. However, sufficiently large and inevitable experimental…

Quantum Physics · Physics 2020-03-18 Haoyu Qi , Daniel J. Brod , Nicolás Quesada , Raúl García-Patrón

A crucial milestone in the field of quantum simulation and computation is to demonstrate that a quantum device can compute certain tasks that are impossible to reproduce by a classical computer with any reasonable resources. Such a…

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

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

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…

Boson Sampling is a task that is conjectured to be computationally hard for a classical computer, but which can be efficiently solved by linear-optical interferometers with Fock state inputs. Significant advances have been reported in the…

Quantum Physics · Physics 2023-04-14 Nicolò Spagnolo , Daniel J. Brod , Ernesto F. Galvão , Fabio Sciarrino

Boson sampling is one of the leading protocols for demonstrating a quantum advantage, but the theory of how this protocol responds to noise is still incomplete. We extend the theory of classical simulation of boson sampling with partial…

Quantum Physics · Physics 2025-03-07 S. N. van den Hoven , E. Kanis , J. J. Renema

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

Although the Schr{\"o}dinger and Heisenberg pictures are equivalent formulations of quantum mechanics, simulations performed choosing one over the other can greatly impact the computational resources required to solve a problem. Here we…

Quantum Physics · Physics 2024-02-27 Dario Cilluffo , Nicola Lorenzoni , Martin B. Plenio

Due to the advances in the manufacturing of quantum hardware in the recent years, significant research efforts have been directed towards employing quantum methods to solving problems in various areas of interest. Thus a plethora of novel…

Gaussian Boson Sampling is a non-universal model for quantum computing inspired by the original formulation of the Boson Sampling problem. Nowadays, it represents a paradigmatic quantum platform to reach the quantum advantage regime in a…

Boson sampling is a mathematical problem that is strongly believed to be intractable for classical computers, whereas passive linear interferometers can produce samples efficiently. So far, the problem remains a computational curiosity, and…

Quantum Physics · Physics 2019-07-04 Georgios M. Nikolopoulos , Thomas Brougham

Boson Sampling is the problem of sampling from the same output probability distribution as a collection of indistinguishable single photons input into a linear interferometer. It has been shown that, subject to certain computational…

Quantum Physics · Physics 2018-06-21 Alexandra E. Moylett , Peter S. Turner