Institute of Quantum Information and Matter, California Institute of Technology, Pasadena, CA 91125
Institute of Quantum Information and Matter, California Institute of Technology, Pasadena, CA 91125.
Proc Natl Acad Sci U S A. 2019 May 7;116(19):9269-9274. doi: 10.1073/pnas.1819316116. Epub 2019 Apr 24.
In this work we demonstrate that nonrandom mechanisms that lead to single-particle localization may also lead to many-body localization, even in the absence of disorder. In particular, we consider interacting spins and fermions in the presence of a linear potential. In the noninteracting limit, these models show the well-known Wannier-Stark localization. We analyze the fate of this localization in the presence of interactions. Remarkably, we find that beyond a critical value of the potential gradient these models exhibit nonergodic behavior as indicated by their spectral and dynamical properties. These models, therefore, constitute a class of generic nonrandom models that fail to thermalize. As such, they suggest new directions for experimentally exploring and understanding the phenomena of many-body localization. We supplement our work by showing that by using machine-learning techniques the level statistics of a system may be calculated without generating and diagonalizing the Hamiltonian, which allows a generation of large statistics.
在这项工作中，我们证明了导致单粒子局域化的非随机机制也可能导致多体局域化，即使在没有无序的情况下也是如此。具体来说，我们考虑了存在线性势的相互作用自旋和费米子。在非相互作用极限下，这些模型表现出众所周知的Wannier-Stark 局域化。我们分析了在相互作用存在的情况下这种局域化的命运。值得注意的是，我们发现，超过势梯度的一个临界值，这些模型表现出非遍历行为，这表明它们的谱和动力学特性。因此，这些模型构成了一类通用的非随机模型，它们不能热化。因此，它们为实验探索和理解多体局域化现象提供了新的方向。我们通过展示可以使用机器学习技术来计算系统的能级统计，而无需生成和对角化哈密顿量，这允许生成大量的统计数据，来补充我们的工作。
