由于单元演变和周期投射测量,旋转配置动态的复杂性
Heitor P Casagrande1, Bo Xing1, Marcello Dalmonte2
1Science, Mathematics and Technology Cluster, Singapore University of Technology and Design, 8 Somapah Road, 487372 Singapore.
Physical review. E
|November 18, 2023
概括
我们分析了经过定期测量的量子系统,揭示了复杂性动态. 随着时间的推移,PCA的复杂性越来越大,为哈密尔顿参数和系统行为提供了洞察力,特别是在不可整合的模型中.
科学领域:
- 量子力学就是量子力学.
- 统计物理学的统计物理.
- 复杂的系统复杂的系统.
背景情况:
- 多体量子系统表现出复杂的动态.
- 定期投射测量引入了概率性的细胞自动机行为.
- 主要组件分析 (PCA) 是一个用于缩小维度和复杂性分析的工具.
研究的目的:
- 在定期测量下,研究量子系统中PCA复杂性的动态.
- 了解哈密尔顿参数和测量协议如何影响系统复杂性.
- 识别可预测PCA复杂性对系统参数敏感性的指标.
主要方法:
- 模拟多体量子系统的哈密尔顿动力学.
- 应用周期性投射测量.
- 使用主要组件分析 (PCA) 描述动态.
- 分析PCA复杂性作为哈密尔顿参数和测量间隔的函数.
主要成果:
- PCA复杂性表现出快速增长,随后在各种哈密尔顿类型 (相互作用,非相互作用,可整合,不可整合) 中出现平原.
- PCA复杂性的动力学对哈密尔顿参数和测量协议敏感.
- 非可整合模型显示PCA复杂性动态对特定系统参数的敏感性较小.
- 提出一个优点的数字来预测PCA复杂性动态的灵敏度.
结论:
- 周期性测量在量子多体系统中诱导复杂的动态.
- PCA复杂性为表征量子系统动态提供了有价值的指标.
- 提出的优点数字有助于预测量子复杂性研究中的系统参数灵敏度.
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