Boson sampling is a computational problem that has recently been proposed as a candidate to obtain an unequivocal quantum computational advantage.The problem consists in sampling from the output distribution of indist...Boson sampling is a computational problem that has recently been proposed as a candidate to obtain an unequivocal quantum computational advantage.The problem consists in sampling from the output distribution of indistinguishable bosons in a linear interferometer.There is strong evidence that such an experiment is hard to classically simulate,but it is naturally solved by dedicated photonic quantum hardware,comprising single photons,linear evolution,and photodetection.This prospect has stimulated much effort resulting in the experimental implementation of progressively larger devices.We review recent advances in photonic boson sampling,describing both the technological improvements achieved and the future challenges.We also discuss recent proposals and implementations of variants of the original problem,theoretical issues occurring when imperfections are considered,and advances in the development of suitable techniques for validation of boson sampling experiments.We conclude by discussing the future application of photonic boson sampling devices beyond the original theoretical scope.展开更多
Gaussian boson sampling is an alternative model for demonstrating quantum computational supremacy,where squeezed states are injected into every input mode, instead of applying single photons as in the case of standard...Gaussian boson sampling is an alternative model for demonstrating quantum computational supremacy,where squeezed states are injected into every input mode, instead of applying single photons as in the case of standard boson sampling. Here by analyzing numerically the computational costs, we establish a lower bound for achieving quantum computational supremacy for a class of Gaussian bosonsampling problems. Specifically, we propose a more efficient method for calculating the transition probabilities, leading to a significant reduction of the simulation costs. Particularly, our numerical results indicate that one can simulate up to 18 photons for Gaussian boson sampling at the output subspace on a normal laptop, 20 photons on a commercial workstation with 256 cores, and about 30 photons for supercomputers. These numbers are significantly smaller than those in standard boson sampling, suggesting that Gaussian boson sampling could be experimentally-friendly for demonstrating quantum computational supremacy.展开更多
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.Her...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 boson sampling can be used to efficiently simulate the work distribution of multiple identical bosons.We link the work distribution to boson sampling and numerically calculate the transition amplitude matrix between the single-boson eigenstates in a one-dimensional quantum piston system,and then map the matrix to a linear optical network of boson sampling.The work distribution can be efficiently simulated by the output probabilities of boson sampling using the method of the grouped probability estimation.The scheme requires at most a polynomial number of the samples and the optical elements.Our work opens up a new path towards the calculation of complex quantum work distribution using only photons and linear optics.展开更多
Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage toward the realization of universal quantum computers.In the context of nonuniversal noi...Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage toward the realization of universal quantum computers.In the context of nonuniversal noisy intermediate quantum devices,photonic-based sampling machines solving the Gaussian boson sampling(GBS)problem currently play a central role in the experimental demonstration of quantum computational advantage.A relevant issue is the validation of the sampling process in the presence of experimental noise,such as photon losses,which could undermine the hardness of simulating the experiment.We test the capability of a validation protocol that exploits the connection between GBS and graph perfect match counting to perform such an assessment in a noisy scenario.In particular,we use as a test bench the recently developed machine Borealis,a large-scale sampling machine that has been made available online for external users,and address its operation in the presence of noise.The employed approach to validation is also shown to provide connections with the open question on the effective advantage of using noisy GBS devices for graph similarity and isomorphism problems and thus provides an effective method for certification of quantum hardware.展开更多
基金The authors declare no conflicts of interest.This work was supported by the European Research Council Advanced Grant CAPABLE(Composite integrated photonic platform by femtosecond laser micromachining,Grant Agreement No.742745)the QuantERA ERA-NET Cofund in Quantum Technologies 2017 project HiPhoP(High-Dimensional Quantum Photonic Platform,Project ID 731473)the European H2020-FETPROACT-2014 Grant QUCHIP(Quantum Simulation on a Photonic Chip,Grant Agreement No.641039).This work was also supported by CNPq project INCT de Informação Quântica.
文摘Boson sampling is a computational problem that has recently been proposed as a candidate to obtain an unequivocal quantum computational advantage.The problem consists in sampling from the output distribution of indistinguishable bosons in a linear interferometer.There is strong evidence that such an experiment is hard to classically simulate,but it is naturally solved by dedicated photonic quantum hardware,comprising single photons,linear evolution,and photodetection.This prospect has stimulated much effort resulting in the experimental implementation of progressively larger devices.We review recent advances in photonic boson sampling,describing both the technological improvements achieved and the future challenges.We also discuss recent proposals and implementations of variants of the original problem,theoretical issues occurring when imperfections are considered,and advances in the development of suitable techniques for validation of boson sampling experiments.We conclude by discussing the future application of photonic boson sampling devices beyond the original theoretical scope.
基金supported by the Guangdong Innovative and Entrepreneurial Research Team Program (2016ZT06D348)Natural Science Foundation of Guangdong Province (2017B030308003)+6 种基金the Key R&D Program of Guangdong Province (2018B030326001)the Science, Technology and Innovation Commission of Shenzhen Municipality (JCYJ20170412152620376, JCYJ20170817105046702 and KYTDPT20181011104202253)the National Natural Science Foundation of China (11875160 and U1801661)supported by the National Natural Science Foundation of China (61832003, 61872334)the Economy, Trade and Information Commission of Shenzhen Municipality (201901161512)the Strategic Priority Research Program of Chinese Academy of Sciences (XDB28000000)K. C. Wong Education Foundation
文摘Gaussian boson sampling is an alternative model for demonstrating quantum computational supremacy,where squeezed states are injected into every input mode, instead of applying single photons as in the case of standard boson sampling. Here by analyzing numerically the computational costs, we establish a lower bound for achieving quantum computational supremacy for a class of Gaussian bosonsampling problems. Specifically, we propose a more efficient method for calculating the transition probabilities, leading to a significant reduction of the simulation costs. Particularly, our numerical results indicate that one can simulate up to 18 photons for Gaussian boson sampling at the output subspace on a normal laptop, 20 photons on a commercial workstation with 256 cores, and about 30 photons for supercomputers. These numbers are significantly smaller than those in standard boson sampling, suggesting that Gaussian boson sampling could be experimentally-friendly for demonstrating quantum computational supremacy.
文摘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 boson sampling can be used to efficiently simulate the work distribution of multiple identical bosons.We link the work distribution to boson sampling and numerically calculate the transition amplitude matrix between the single-boson eigenstates in a one-dimensional quantum piston system,and then map the matrix to a linear optical network of boson sampling.The work distribution can be efficiently simulated by the output probabilities of boson sampling using the method of the grouped probability estimation.The scheme requires at most a polynomial number of the samples and the optical elements.Our work opens up a new path towards the calculation of complex quantum work distribution using only photons and linear optics.
基金supported by the ERC Advanced Grant QU-BOSS(QUantum advantage via nonlinear BOSon Sampling,Grant No.884676)by ICSC-Centro Nazionale di Ricerca in High Performance Computing,Big Data,and Quantum Computing,funded by the European Union-NextGenerationEU.D.S.acknowledges Thales Alenia Space Italia for supporting the PhD fellowship.N.S.acknowledges funding from Sapienza Universitàdi Roma via Bando Ricerca 2020:Progetti di Ricerca Piccoli,Project No.RP120172B8A36B37.
文摘Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage toward the realization of universal quantum computers.In the context of nonuniversal noisy intermediate quantum devices,photonic-based sampling machines solving the Gaussian boson sampling(GBS)problem currently play a central role in the experimental demonstration of quantum computational advantage.A relevant issue is the validation of the sampling process in the presence of experimental noise,such as photon losses,which could undermine the hardness of simulating the experiment.We test the capability of a validation protocol that exploits the connection between GBS and graph perfect match counting to perform such an assessment in a noisy scenario.In particular,we use as a test bench the recently developed machine Borealis,a large-scale sampling machine that has been made available online for external users,and address its operation in the presence of noise.The employed approach to validation is also shown to provide connections with the open question on the effective advantage of using noisy GBS devices for graph similarity and isomorphism problems and thus provides an effective method for certification of quantum hardware.
