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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

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

Boson Sampling represents a promising witness of the supremacy of quantum systems as a resource for the solution of computational problems. The classical hardness of Boson Sampling has been related to the so called Permanent-of-Gaussians…

Quantum Physics · Physics 2015-12-01 Ludovico Latmiral

Boson sampling has been theoretically proposed and experimentally demonstrated to show quantum computational advantages. However, it still lacks the deep understanding of the practical applications of boson sampling. Here we propose that…

Quantum Physics · Physics 2023-11-10 Wen-Qiang Liu , Zhang-qi Yin

We study the quantum to classical transition in Boson Sampling by analysing how $N$-boson interference is affected by inevitable noise in an experimental setup. We adopt the Gaussian noise model of Kalai and Kindler for Boson Sampling and…

Quantum Physics · Physics 2019-07-31 Valery Shchesnovich

We demonstrate how boson sampling with photons of partial distinguishability can be expressed in terms of interference of fewer photons. We use this observation to propose a classical algorithm to simulate the output of a boson sampler fed…

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

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

We study the classical complexity of the exact Boson Sampling problem where the objective is to produce provably correct random samples from a particular quantum mechanical distribution. The computational framework was proposed by Aaronson…

Data Structures and Algorithms · Computer Science 2017-10-19 Peter Clifford , Raphaël Clifford

When the problem of boson sampling was first proposed, it was assumed that little or no photon collisions occur. However, modern experimental realizations rely on setups where collisions are quite common, i.e. the number of photons $M$…

Quantum Physics · Physics 2023-02-08 M. Umanskii , A. N. Rubtsov

Boson-sampling is a highly simplified, but non-universal, approach to implementing optical quantum computation. It was shown by Aaronson and Arkhipov that this protocol cannot be efficiently classically simulated unless the polynomial…

Quantum Physics · Physics 2014-05-27 Peter P. Rohde , Keith R. Motes , Paul A. Knott , William J. Munro

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

BosonSampling is a quantum mechanical task involving Fock basis state preparation and detection and evolution using only linear interactions. A classical algorithm for producing samples from this quantum task cannot be efficient unless the…

Quantum Physics · Physics 2017-08-09 A. P. Lund , S. Rahimi-Keshari , T. C. Ralph

Boson sampling is a problem intractable for classical computers, but can be naturally solved on a specialized photonic quantum simulator which requires less resources than building a universal quantum computer. The biggest challenge to…

The boson sampling problem has triggered a lot of interest in the scientific community because of its potential of demonstrating the computational power of quantum interference without the need of non-linear processes. However, the…

Quantum Physics · Physics 2015-12-18 Vincenzo Tamma , Simon Laibacher

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

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

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…

Since its introduction Boson Sampling has been the subject of intense study in the world of quantum computing. The task is to sample independently from the set of all $n \times n$ submatrices built from possibly repeated rows of a larger $m…

Quantum Physics · Physics 2020-05-27 Peter Clifford , Raphaël Clifford

Sampling from probability distributions of quantum circuits is a fundamentally and practically important task which can be used to demonstrate quantum supremacy using noisy intermediate-scale quantum devices. In the present work, we examine…

Quantum Physics · Physics 2022-08-29 Changhun Oh , Youngrong Lim , Bill Fefferman , Liang Jiang