Efficient classical simulation of continuous variable quantum information processes

被引:299
|
作者
Bartlett, SD [1 ]
Sanders, BC
Braunstein, SL
Nemoto, K
机构
[1] Macquarie Univ, Dept Phys, Sydney, NSW 2109, Australia
[2] Macquarie Univ, Ctr Adv Comp Algorithms & Cryptog, Sydney, NSW 2109, Australia
[3] Bangor Univ, Bangor LL57 1UT, Gwynedd, Wales
关键词
D O I
10.1103/PhysRevLett.88.097904
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We obtain sufficient conditions for the efficient simulation of a continuous variable quantum algorithm or process on a classical computer. The resulting theorem is an extension of the Gottesman-Knill theorem to continuous variable quantum information. For a collection of harmonic oscillators, any quantum process that begins with unentangled Gaussian states, performs only transformations generated by Hamiltonians that are quadratic in the canonical operators, and involves only measurements of canonical operators (including finite losses) and suitable operations conditioned on these measurements can be simulated efficiently on a classical computer.
引用
收藏
页码:4 / 979044
页数:4
相关论文
共 50 条
  • [1] Efficient classical simulation of optical quantum information circuits
    Bartlett, SD
    Sanders, BC
    PHYSICAL REVIEW LETTERS, 2002, 89 (20)
  • [2] Efficient classical simulation of measurements in optical quantum information
    Bartlett, SD
    Sanders, BC
    QUANTUM COMMUNICATION, MEASUREMENT AND COMPUTING, PROCEEDINGS, 2003, : 430 - 433
  • [3] Efficient Classical Simulation and Benchmarking of Quantum Processes in the Weyl Basis
    Franca, Daniel Stilck
    Strelchuk, Sergii
    Studzinski, Michal
    PHYSICAL REVIEW LETTERS, 2021, 126 (21)
  • [4] Semigroup techniques for the efficient classical simulation of optical quantum information
    Bartlett, SD
    GROUP 24 : PHYSICAL AND MATHEMATICAL ASPECTS OF SYMMETRIES, 2003, 173 : 497 - 500
  • [5] Anonymous broadcasting of classical information with a continuous-variable topological quantum code
    Menicucci, Nicolas C.
    Baragiola, Ben Q.
    Demarie, Tommaso F.
    Brennen, Gavin K.
    PHYSICAL REVIEW A, 2018, 97 (03)
  • [7] Continuous-Variable Deep Quantum Neural Networks for Flexible Learning of Structured Classical Information
    Basani, Jasvith Raj
    Bhattacherjee, Aranya
    COMMUNICATIONS IN COMPUTATIONAL PHYSICS, 2021, 30 (04) : 1216 - 1231
  • [8] Noiseless and efficient quantum information transmission for fiber-based continuous-variable quantum networks
    Qin, Jiliang
    Cheng, Jialin
    Liang, Shaocong
    Yan, Zhihui
    Lu, Huadong
    Jia, Xiaojun
    PHYSICAL REVIEW APPLIED, 2024, 21 (06):
  • [9] Fisher Information with Continuous Variable Quantum Resources
    Atkinson, George S.
    Allen, Euan J.
    Ferranti, Giacomo
    Matthews, Jonathan C. F.
    2019 CONFERENCE ON LASERS AND ELECTRO-OPTICS EUROPE & EUROPEAN QUANTUM ELECTRONICS CONFERENCE (CLEO/EUROPE-EQEC), 2019,
  • [10] Continuous-variable quantum information processing
    Andersen, Ulrik L.
    Leuchs, Gerd
    Silberhorn, Christine
    LASER & PHOTONICS REVIEWS, 2010, 4 (03) : 337 - 354