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摘要翻译：
我们证明了张量网络态的形式，如矩阵积态(MPS)可以作为变分量子蒙特卡罗模拟的基础。利用随机优化方法，利用周期边界条件和D为48的D*D矩阵，对临界自旋为n=256的横向伊辛链进行了显式的MPS计算，证明了这种方法的潜力。对于周期系统，我们的格式的计算量为Nd^3，而标准的MPS方法和相关的密度矩阵重罗姆化群方法的计算量分别为Nd^5和Nd^6。
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英文标题：
《Variational quantum Monte Carlo simulations with tensor-network states》
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作者：
A. W. Sandvik and G. Vidal
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最新提交年份：
2007
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分类信息：
一级分类：Physics 物理学
二级分类：Strongly Correlated Electrons 强关联电子
分类描述：Quantum magnetism, non-Fermi liquids, spin liquids, quantum criticality, charge density waves, metal-insulator transitions
量子磁学，非费米液体，自旋液体，量子临界性，电荷密度波，金属-绝缘体跃迁
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一级分类：Physics 物理学
二级分类：Statistical Mechanics 统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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英文摘要：
We show that the formalism of tensor-network states, such as the matrix product states (MPS), can be used as a basis for variational quantum Monte Carlo simulations. Using a stochastic optimization method, we demonstrate the potential of this approach by explicit MPS calculations for the transverse Ising chain with up to N=256 spins at criticality, using periodic boundary conditions and D*D matrices with D up to 48. The computational cost of our scheme formally scales as ND^3, whereas standard MPS approaches and the related density matrix renromalization group method scale as ND^5 and ND^6, respectively, for periodic systems.
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PDF链接：
https://arxiv.org/pdf/708.2232
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