提取非马科夫式开放量子系统的动态图
David J Strachan1, Archak Purkayastha2,3, Stephen R Clark1
1H. H. Wills Physics Laboratory, University of Bristol, Bristol BS8 1TL, United Kingdom.
The Journal of chemical physics
|October 16, 2024
概括
本研究开发了一种张量子网络方法,从与热浴相结合的系统中准确地提取量子动态图 (Λ̂(τ)). 该方法揭示了内存时间层次结构,使开放量子系统能够更快地计算静态状态.
科学领域:
- 量子力学就是量子力学.
- 凝聚物质物理学 凝聚物质物理学
- 量子信息理论就是量子信息理论.
背景情况:
- 量子进化是由动态地图 (Λ̂(τ) 描述的,当系统与热浴相结合时,这些地图通常是非马科夫的.
- 评估非马科夫动态和提取准确的动态图是计算上具有挑战性的,特别是没有明确的时间尺度分离.
- 假设一个独特的稳定状态意味着浴室内内存时间有限.
研究的目的:
- 开发一个张量网络框架,用于直接和准确地提取与热浴相结合的系统的量子动态图 (Λ̂(τ)) .
- 研究非马科夫动力学,并为开放的量子系统建立内存时间层次结构.
- 通过识别相关的时间尺度,使静止状态的有效计算成为可能.
主要方法:
- 使用直角多项式映射和热场加倍来创建无限费米浴的净化链表征.
- 采用Choi-Jamiolkowski等态来从纯状态计算中重建动态图 (Λ̂(τ)).
- 计算了时间局部传播器 (L̂(τ)) 并分析了固定点收以确定内存时间 (τmΛ, τmL).
主要成果:
- 成功地提取了与费米浴相结合的相互作用费米离子模式的动态地图 (Λ̂(τ)) 和时间局部传播器 (L̂(τ)).
- 建立了记忆时间层次: τmL ≤ τmΛ ≤ τre,其中 τre 是特征性的放松时间.
- 在确定像安德森杂质模型这样的模型的静态状态时,证明了显著的加快速度.
结论:
- 开发的张量网络方法准确地捕捉了非马科夫动态,并提供了对开放量子系统的深刻分析.
- 识别的内存时间层次提供了一条有效计算长期稳定状态的途径,绕过直接的长期模拟.
- 这种方法在放松时间明显超过浴记忆时间的疗法中尤其有利.
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