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非监督学习高维多体波函数矢量轨迹所在低维子空间

黄志伟 杨宏宇 翟峰 陆肖励 卢军强 吴健

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非监督学习高维多体波函数矢量轨迹所在低维子空间

黄志伟, 杨宏宇, 翟峰, 陆肖励, 卢军强, 吴健

Low-dimensional trajectory subspace of high-dimensional many-body wavefunctions by unsupervised learning

Huang Zhi-Wei, Yang Hong-Yu, Zhai Feng, Lu Xiao-Li, Lu Jun-Qiang, Wu Jian
cstr: 32037.14.aps.70.20210697
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  • Frame等提出采用特征矢量延拓方法求解关联量子模型的高维多体波函数: 当模型哈密顿矩阵包含光滑变化的参数时, 其特征矢量随参数变化的轨迹集中在1个低维的子空间中, 因此可以将哈密顿量投影到该子空间的一组基矢量来简化求解(Frame D, He R Z, Ipsen I, Lee D, Lee D, Rrapaj E 2018 Phys. Rev. Lett. 121 032501). 但是他们没有明确给出轨迹子空间的维度以及其与模型大小之间的联系. 本文系统研究了大小不同的反铁磁Heisenberg链模型, 其交换相互作用随参数光滑变化. 首先通过主成分分析方法分别确定了包含4个自旋的模型和包含6个自旋的模型的基态多体波函数矢量轨迹子空间, 并分别绘制了子空间中的轨迹. 然后分析了包含$8,\cdots ,14$个自旋的模型基态矢量轨迹的主成分分量, 并指出: 当采用特征矢量延拓方法求解反铁磁Heisenberg链模型基态时, 所需基矢数目随模型所包含自旋个数的增加而增加. 本文研究可用于指导采用特征矢量延拓方法求解包含更多自旋的反铁磁Heisenberg链模型哈密顿量.
    Frame et al. (Frame D, He R Z, Ipsen I, Lee D, Lee D, Rrapaj E 2018 Phys. Rev. Lett. 121 032501) proposed to use eigenvector continuation to solve high-dimensional many-body wavefunctions of relevant quantum models. When a model’s Hamiltonian matrix includes smoothly varying parameters, the corresponding eigenvector trajectory spans only a low-dimensional subspace. Therefore, it is possible to simplify the calculations by projecting the Hamiltonian onto a set of basis vectors of this subspace. However, the dimension of the trajectory subspace and its relationship with the size of the model are still unclear. In this paper, we study the antiferromagnetic Heisenberg chain models of different sizes systematically; their exchange interactions change with parameters smoothly. We first use principal component analysis to determine the subspaces of ground state many-body wavefunction vector trajectories of a 4-spin model and a 6-spin model, and plot the trajectories in the subspaces, respectively; we then analyze the principal components of ground state vector trajectories of models including $8,\cdots ,14$ spins, and reveal that when using eigenvector continuation to solve the ground state of an antiferromagnetic Heisenberg chain model, the number of basis vectors required increases with the number of spins in the model increasing. Our study can guide the application of eigenvector continuation in solving the Hamiltonian of a Heisenberg chain model containing more spins.
      Corresponding author: Lu Jun-Qiang, anyeon@foxmail.com ; Wu Jian, wu@phys.tsinghua.edu.cn
    [1]

    Mezzacapo F, Schuch N, Boninsegni M, Cirac J I 2009 New J. Phys. 11 083026Google Scholar

    [2]

    Beach M J S, Melko R G, Grover T, Hsieh T H 2019 Phys. Rev. B 100 094434Google Scholar

    [3]

    Anders S, Plenio M B, Dür W, Verstraete F, Briegel H J 2006 Phys. Rev. Lett. 97 107206Google Scholar

    [4]

    Girardeau M D 1990 Phys. Rev. A 42 3303Google Scholar

    [5]

    Liu J W, Qi Y, Meng Z Y, Fu L 2017 Phys. Rev. B 95 041101Google Scholar

    [6]

    Elhatisari S, Epelbaum E, Krebs H, Lahde T A, Lee D, Li N, Lu B N, Meibner U G, Rupak G 2017 Phys. Rev. Lett. 119 222505Google Scholar

    [7]

    Baumgärtner A, Burkitt A N, Burkitt A N, Ceperley D M, De Raedt H, Ferrenberg A M, Heermann D W, Herrmann H J, Landau D P, Levesque D, Linden W, Reger F D, Schmidt K E, Selke W, Stauffer D, Swendsen R H, Wang J S, Weis J J, Young A P 2012 The Monte Carlo Method in Condensed Matter Physics (Springer Science & Business Media) pp23−51

    [8]

    Dawson C M, Eisert J, Osborne T J 2008 Phys. Rev. Lett. 100 130501Google Scholar

    [9]

    Needs R J, Towler M D, Drummond N D, López Ríos P 2009 J. Phys.: Condens. Matter 22 023201Google Scholar

    [10]

    Ceperley D M, Alder B J 1980 Phys. Rev. Lett. 45 566Google Scholar

    [11]

    Sandvik A W, Kurkijärvi J 1991 Phys. Rev. B 43 5950Google Scholar

    [12]

    Gelfand M P, Singh R R P 2000 Adv. Phys. 49 93Google Scholar

    [13]

    Oitmaa J, Hamer C, Zheng W 2006 Series Expansion Methods for Strongly Interacting Lattice Models (Cambridge: Cambridge University Press) pp99−123

    [14]

    Lanczos C 1950 J. Res. Nat. Bur. Stand. 45 255Google Scholar

    [15]

    Saad Y 2011 Numerical Methods for Large Eigenvalue Problems, Classics in Applied Mathematics (Philadelphia: Society for Industrial and Applied Mathematic) pp125−162

    [16]

    Frame D, He R Z, Ipsen I, Lee D, Lee D, Rrapaj E 2018 Phys. Rev. Lett. 121 032501Google Scholar

    [17]

    Wang L 2016 Phys. Rev. B 94 195105Google Scholar

    [18]

    Hu W J, Singh R R P, Scalettar R T 2017 Phys. Rev. E 95 062122Google Scholar

    [19]

    Wang C, Zhai H 2017 Phys. Rev. B 96 144432Google Scholar

    [20]

    Wang C, Zhai H 2018 Front. Phys. 13 130507Google Scholar

  • 图 1  一维Heisenberg链模型示意图

    Fig. 1.  Schematic diagram of a one-dimensional Heisenberg chain model.

    图 2  $ L=4 $的Heisenberg链 (a) 基态矢量随$ \theta $变化的轨迹(从红到蓝是0°到90°); (b) 在6维和2维空间中分别求得的基态能量

    Fig. 2.  The Heisenberg chain with $ L=4 $: (a) Ground state vector trajectory (from red to blue: θ = 0° to θ = 90°); (b) ground state energies calculated in a 6-dimensional space and in a 2-dimensioanl space, respectively.

    图 3  $ L=6 $的Heisenberg链 (a) 基态矢量随$ \theta $变化的轨迹(从红到蓝是0°到90°); (b) 在20维和3维空间中分别求得的基态能量

    Fig. 3.  The Heisenberg chain with $ L=6 $: (a) Ground state vector trajectory (from red to blue: θ = 0° to θ = 90°); (b) ground state energies calculated in a 20-dimensional space and in a 3-dimensioanl space, respectively.

    图 4  (a) 采用特征矢量延拓方法求解随$ \theta $变化的Heisenberg链基态能量所需基矢数目与其所含自旋个数之间的关系; (b) $ L=16 $的Heisenberg链在10维和6维空间中分别求得的基态能量

    Fig. 4.  (a) Relationship between the number of basis vectors needed to calculate $ \theta $-dependent ground state energies of the Heisenberg chain by eigenvector continuation and the number of spins in the chain; (b) ground state energies of the Heisenberg chain with $ L=16 $ calculated in a 10-dimensional space and in a 6-dimensioanl space, respectively.

    Baidu
  • [1]

    Mezzacapo F, Schuch N, Boninsegni M, Cirac J I 2009 New J. Phys. 11 083026Google Scholar

    [2]

    Beach M J S, Melko R G, Grover T, Hsieh T H 2019 Phys. Rev. B 100 094434Google Scholar

    [3]

    Anders S, Plenio M B, Dür W, Verstraete F, Briegel H J 2006 Phys. Rev. Lett. 97 107206Google Scholar

    [4]

    Girardeau M D 1990 Phys. Rev. A 42 3303Google Scholar

    [5]

    Liu J W, Qi Y, Meng Z Y, Fu L 2017 Phys. Rev. B 95 041101Google Scholar

    [6]

    Elhatisari S, Epelbaum E, Krebs H, Lahde T A, Lee D, Li N, Lu B N, Meibner U G, Rupak G 2017 Phys. Rev. Lett. 119 222505Google Scholar

    [7]

    Baumgärtner A, Burkitt A N, Burkitt A N, Ceperley D M, De Raedt H, Ferrenberg A M, Heermann D W, Herrmann H J, Landau D P, Levesque D, Linden W, Reger F D, Schmidt K E, Selke W, Stauffer D, Swendsen R H, Wang J S, Weis J J, Young A P 2012 The Monte Carlo Method in Condensed Matter Physics (Springer Science & Business Media) pp23−51

    [8]

    Dawson C M, Eisert J, Osborne T J 2008 Phys. Rev. Lett. 100 130501Google Scholar

    [9]

    Needs R J, Towler M D, Drummond N D, López Ríos P 2009 J. Phys.: Condens. Matter 22 023201Google Scholar

    [10]

    Ceperley D M, Alder B J 1980 Phys. Rev. Lett. 45 566Google Scholar

    [11]

    Sandvik A W, Kurkijärvi J 1991 Phys. Rev. B 43 5950Google Scholar

    [12]

    Gelfand M P, Singh R R P 2000 Adv. Phys. 49 93Google Scholar

    [13]

    Oitmaa J, Hamer C, Zheng W 2006 Series Expansion Methods for Strongly Interacting Lattice Models (Cambridge: Cambridge University Press) pp99−123

    [14]

    Lanczos C 1950 J. Res. Nat. Bur. Stand. 45 255Google Scholar

    [15]

    Saad Y 2011 Numerical Methods for Large Eigenvalue Problems, Classics in Applied Mathematics (Philadelphia: Society for Industrial and Applied Mathematic) pp125−162

    [16]

    Frame D, He R Z, Ipsen I, Lee D, Lee D, Rrapaj E 2018 Phys. Rev. Lett. 121 032501Google Scholar

    [17]

    Wang L 2016 Phys. Rev. B 94 195105Google Scholar

    [18]

    Hu W J, Singh R R P, Scalettar R T 2017 Phys. Rev. E 95 062122Google Scholar

    [19]

    Wang C, Zhai H 2017 Phys. Rev. B 96 144432Google Scholar

    [20]

    Wang C, Zhai H 2018 Front. Phys. 13 130507Google Scholar

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  • 被引次数: 0
出版历程
  • 收稿日期:  2021-04-13
  • 修回日期:  2021-08-31
  • 上网日期:  2021-09-07
  • 刊出日期:  2021-12-20

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