发表机构
TU Dortmund（多特蒙德工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出CTEMPO张量网络路径积分方案，通过压缩键维数实现强耦合非马尔可夫开放量子网络的数值精确模拟，在自旋-玻色子模型和7位点FMO复合体上验证了数量级改进，并探索了20个量子点的超辐射标度行为。
AI 中文摘要
非马尔可夫开放量子网络是量子理论中最具挑战性的问题之一，因为它们同时遭受指数级扩展的多体态空间以及当位点与结构化环境强耦合时长的记忆时间的影响。最近通过将张量网络与实时路径积分相结合来解决这些问题的努力，例如TEMPO和过程张量，仅限于系统-环境耦合相当弱的系统，因为强耦合导致大的键维数。在这里，我们设计了一种张量网络方案（CTEMPO），对于单位点问题产生特别小的键维数。然后我们将其扩展为一种实用的方案，通过时间演化相应的梳状张量网络来模拟非马尔可夫量子网络。在自旋-玻色子模型上对单位点算法进行基准测试，我们发现相对于已有方法有数量级的改进。多站点算法被证明能够解决臭名昭著的7位点Fenna-Matthews-Olson光合复合体的难题，其光谱密度包含62个峰。然后我们应用我们的方法来探索多达$N=20$个量子点分别耦合到超欧姆声子浴的超辐射的标度行为。我们的方法为非马尔可夫量子网络提供了一种交钥匙解决方案，并且与更一般的张量网络拓扑兼容。
英文摘要
Non-Markovian open quantum networks are among the most challenging problems in quantum theory, as they suffer from both, the exponentially scaling many-body state space as well as long memory times when the sites are strongly coupled to structured environments. Recent efforts to address them by combining tensor networks with real-time path integrals, such as TEMPO and process tensors, were however limited to systems with rather weak system-environment couplings because strong couplings lead to large bond dimensions. Here, we devise a tensor network scheme (CTEMPO) resulting in particularly small bond dimensions for single-site problems. We then extend this to a practical scheme to simulate non-Markovian quantum networks by time-evolving a corresponding comb tensor network. Benchmarking the single-site algorithm on the spin-boson model we find orders-of-magnitude improvement over established methods. The multi-site algorithm is shown to solve the notoriously difficult problem of the 7-site Fenna-Matthews-Olson photosynthetic complex, whose spectral density contains 62 peaks. We then apply our approach to explore the scaling behavior of the superradiance of up to $N=20$ quantum dots individually coupled to super-Ohmic phonon baths. Our approach provides a turnkey solution to non-Markovian quantum networks and is compatible with more general tensor network topologies.
Comments7 pages, 4 figures + 4 pages, 2 figures SM
