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具有定向更新方案的晶格哈密顿量的蠕动量子蒙特卡罗算法

Reptation quantum Monte Carlo algorithm for lattice Hamiltonians with a directed-update scheme.

作者信息

Carleo Giuseppe, Becca Federico, Moroni Saverio, Baroni Stefano

机构信息

Scuola Internazionale Superiore di Studi Avanzati and Democritos National Simulation Center, Istituto Officina dei Materiali del CNR, Via Bonomea 265, I-34136 Trieste, Italy.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Oct;82(4 Pt 2):046710. doi: 10.1103/PhysRevE.82.046710. Epub 2010 Oct 25.

Abstract

We provide an extension to lattice systems of the reptation quantum Monte Carlo algorithm, originally devised for continuous Hamiltonians. For systems affected by the sign problem, a method to systematically improve upon the so-called fixed-node approximation is also proposed. The generality of the method, which also takes advantage of a canonical worm algorithm scheme to measure off-diagonal observables, makes it applicable to a vast variety of quantum systems and eases the study of their ground-state and excited-state properties. As a case study, we investigate the quantum dynamics of the one-dimensional Heisenberg model and we provide accurate estimates of the ground-state energy of the two-dimensional fermionic Hubbard model.

摘要

我们对原本为连续哈密顿量设计的蠕动量子蒙特卡罗算法进行了扩展,使其适用于晶格系统。对于受符号问题影响的系统,我们还提出了一种系统地改进所谓固定节点近似的方法。该方法具有通用性,还利用了规范蠕虫算法方案来测量非对角可观测量,使其适用于各种各样的量子系统,并简化了对其基态和激发态性质的研究。作为一个案例研究,我们研究了一维海森堡模型的量子动力学,并给出了二维费米子哈伯德模型基态能量的精确估计。

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