Literature DB >> 29219463

Gaussian Boson Sampling.

Craig S Hamilton1, Regina Kruse2, Linda Sansoni2, Sonja Barkhofen2, Christine Silberhorn2, Igor Jex1.   

Abstract

Boson sampling has emerged as a tool to explore the advantages of quantum over classical computers as it does not require universal control over the quantum system, which favors current photonic experimental platforms. Here, we introduce Gaussian Boson sampling, a classically hard-to-solve problem that uses squeezed states as a nonclassical resource. We relate the probability to measure specific photon patterns from a general Gaussian state in the Fock basis to a matrix function called the Hafnian, which answers the last remaining question of sampling from Gaussian states. Based on this result, we design Gaussian Boson sampling, a #P hard problem, using squeezed states. This demonstrates that Boson sampling from Gaussian states is possible, with significant advantages in the photon generation probability, compared to existing protocols.

Year:  2017        PMID: 29219463     DOI: 10.1103/PhysRevLett.119.170501

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  11 in total

1.  Quantum experiments and graphs II: Quantum interference, computation, and state generation.

Authors:  Xuemei Gu; Manuel Erhard; Anton Zeilinger; Mario Krenn
Journal:  Proc Natl Acad Sci U S A       Date:  2019-02-15       Impact factor: 11.205

2.  Photonic chip brings optical quantum computers a step closer.

Authors:  Ulrik L Andersen
Journal:  Nature       Date:  2021-03       Impact factor: 49.962

3.  Loops simplify a set-up to boost quantum computational advantage.

Authors:  Daniel Jost Brod
Journal:  Nature       Date:  2022-06       Impact factor: 69.504

4.  Classical simulation of boson sampling with sparse output.

Authors:  Wojciech Roga; Masahiro Takeoka
Journal:  Sci Rep       Date:  2020-09-07       Impact factor: 4.379

5.  Quantum computational advantage via high-dimensional Gaussian boson sampling.

Authors:  Abhinav Deshpande; Arthur Mehta; Trevor Vincent; Nicolás Quesada; Marcel Hinsche; Marios Ioannou; Lars Madsen; Jonathan Lavoie; Haoyu Qi; Jens Eisert; Dominik Hangleiter; Bill Fefferman; Ish Dhand
Journal:  Sci Adv       Date:  2022-01-05       Impact factor: 14.136

6.  Generalized concurrence in boson sampling.

Authors:  Seungbeom Chin; Joonsuk Huh
Journal:  Sci Rep       Date:  2018-04-17       Impact factor: 4.379

7.  Near-ideal spontaneous photon sources in silicon quantum photonics.

Authors:  S Paesani; M Borghi; S Signorini; A Maïnos; L Pavesi; A Laing
Journal:  Nat Commun       Date:  2020-05-19       Impact factor: 14.919

8.  The boundary for quantum advantage in Gaussian boson sampling.

Authors:  Jacob F F Bulmer; Bryn A Bell; Rachel S Chadwick; Alex E Jones; Diana Moise; Alessandro Rigazzi; Jan Thorbecke; Utz-Uwe Haus; Thomas Van Vaerenbergh; Raj B Patel; Ian A Walmsley; Anthony Laing
Journal:  Sci Adv       Date:  2022-01-26       Impact factor: 14.136

9.  Molecular docking with Gaussian Boson Sampling.

Authors:  Leonardo Banchi; Mark Fingerhuth; Tomas Babej; Christopher Ing; Juan Miguel Arrazola
Journal:  Sci Adv       Date:  2020-06-05       Impact factor: 14.136

10.  Dissipation-Induced Information Scrambling in a Collision Model.

Authors:  Yan Li; Xingli Li; Jiasen Jin
Journal:  Entropy (Basel)       Date:  2022-02-27       Impact factor: 2.524

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