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arXiv 1807.07577cond-mat.stat-mechcond-mat.dis-nncond-mat.quant-gas
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多体量子系统中的无扰和弛豫时间尺度

Thouless and relaxation time scales in many-body quantum systems

Mauro Schiulaz, E. Jonathan Torres-Herrera, Lea F. Santos

摘要:

在非平衡量子动力学研究中,一个主要的开放问题是识别包含许多相互作用粒子的孤立量子系统的弛豫过程中所涉及的时间尺度。我们表明,长时间尺度可以分析发现,通过分析动力学表现的光谱相关性。使用这种方法,我们表明,无扰时间,$t_{\text{Th}}$,和弛豫时间,$t_{\text{R}}$,随系统大小呈指数增长。我们定义$t_{\text{Th}}$为初始状态在多体希尔伯特空间中的传播完成的时间,并验证它与无量纲能量的倒数一致。$t_{\text{Th}}$标志着动力学获得普遍特征的点,而弛豫发生在演化达到稳态时。在混沌系统中,$t_{\text{Th}}\ll t_{\text{R}}$,而对于接近多体局域相的系统,$t_{\text{Th}}\rightarrow t_{\text{R}}$。我们的分析结果$t_{\text{Th}}$和$t_{\text{R}}$的生存概率,这是一个全球性的数量。我们数值计算表明,相同的时间尺度也出现在自旋自相关函数,这是一个实验的本地观察的演变。我们的研究是针对现实的多体量子模型进行的。结果与随机矩阵的结果进行了比较。

英文摘要:

A major open question in studies of nonequilibrium quantum dynamics is the identification of the time scales involved in the relaxation process of isolated quantum systems that have many interacting particles. We demonstrate that long time scales can be analytically found by analyzing dynamical manifestations of spectral correlations. Using this approach, we show that the Thouless time, $t_{\text{Th}}$, and the relaxation time, $t_{\text{R}}$, increase exponentially with system size. We define $t_{\text{Th}}$ as the time at which the spread of the initial state in the many-body Hilbert space is complete and verify that it agrees with the inverse of the Thouless energy. $t_{\text{Th}}$ marks the point beyond which the dynamics acquire universal features, while relaxation happens later when the evolution reaches a stationary state. In chaotic systems, $t_{\text{Th}}\ll t_{\text{R}}$, while for systems approaching a many-body localized phase, $t_{\text{Th}}\rightarrow t_{\text{R}}$. Our analytical results for $t_{\text{Th}}$ and $t_{\text{R}}$ are obtained for the survival probability, which is a global quantity. We show numerically that the same time scales appear also in the evolution of the spin autocorrelation function, which is an experimental local observable. Our studies are carried out for realistic many-body quantum models. The results are compared with those for random matrices.

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