格点哈密顿量的直接更新蠕动量子蒙特卡罗方法
Reptation quantum Monte Carlo for lattice Hamiltonians with a directed-update scheme
摘要：
我们提供了一个扩展到晶格系统的爬行量子蒙特卡罗算法，最初设计的连续哈密顿。对于受符号问题影响的系统，还提出了一种系统地改进所谓的固定节点近似的方法。该方法的通用性，它也利用了一个典型的蠕虫算法计划来测量非对角可观测量，使其适用于各种各样的量子系统，并简化了研究其基态和激发态的属性。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，我们提供了精确的估计的基态能量的二维费米子哈伯德模型。
英文摘要：
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-states 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.
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