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arXiv 2407.12909cond-mat.stat-mechcond-mat.dis-nnquant-ph
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动力学约束模型中的状态依赖迁移率边

State-dependent mobility edge in kinetically constrained models

Manthan Badbaria, Nicola Pancotti, Rajeev Singh, Jamir Marino, Riccardo J. Valencia-Tortora

AI总结:

本文提出动力学约束的量子 East 模型中存在状态依赖迁移率边,通过张量网络模拟发现低能密度下键维数呈多项式增长,揭示了非热态本征态导致的缓慢纠缠增长机制。

摘要:

在这项工作中,我们展示了动力学约束的量子 East 模型介于量子疤痕系统和多体局域化系统之间,其能谱中表现出一种非常规的迁移率边。我们将此场景命名为$\ extit{状态依赖}$迁移率边:尽管系统在热态和非热态本征态之间没有表现出明显的能量分离,但非热态本征态的丰富性导致许多初始状态(如乘积态)在有限能量密度以下表现出缓慢的纠缠增长。我们通过使用张量网络模拟动力学来表征这种状态依赖迁移率边,系统尺寸远超精确对角化可处理的范围。聚焦于初始乘积态,我们观察到所需键维数随其能量密度函数的动力学定性变化。具体而言,在达到特定能量密度之前,键维数通常随时间呈$\ extit{多项式}$增长,我们将该能量密度定位为状态依赖迁移率边,从而实现长时间的模拟。在此能量密度之上,键维数通常呈$\ extit{指数}$增长,使得模拟在短时间后实际上不可行,这与相互作用理论中的普遍预期一致。我们将键维数的多项式增长与该能量密度附近大量非热态本征态的存在相关联,并通过张量网络计算了其中的一个子集。我们的研究结果还涉及量子采样问题以及 Clifford 族以外量子线路的高效模拟。

英文摘要:

In this work, we show that the kinetically constrained quantum East model lies between a quantum scarred and a many-body localized system featuring an unconventional type of mobility edge in the spectrum. We name this scenario $\textit{state-dependent}$ mobility edge: while the system does not exhibit a sharp separation in energy between thermal and non-thermal eigenstates, the abundance of non-thermal eigenstates results in slow entanglement growth for $\textit{many}$ initial states, such as product states, below a finite energy density. We characterize the state-dependent mobility edge by looking at the complexity of classically simulating dynamics using tensor network for system sizes well beyond those accessible via exact diagonalization. Focusing on initial product states, we observe a qualitative change in the dynamics of the bond dimension needed as a function of their energy density. Specifically, the bond dimension typically grows $\textit{polynomially}$ in time up to a certain energy density, where we locate the state-dependent mobility edge, enabling simulations for long times. Above this energy density, the bond dimension typically grows $\textit{exponentially}$ making the simulation practically unfeasible beyond short times, as generally expected in interacting theories. We correlate the polynomial growth of the bond dimension to the presence of many non-thermal eigenstates around that energy density, a subset of which we compute via tensor network. The outreach of our findings encompasses quantum sampling problems and the efficient simulation of quantum circuits beyond Clifford families.

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