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基于无限张量网络收缩的开放量子系统动力学

Open Quantum System Dynamics from Infinite Tensor Network Contraction.

作者信息

Link Valentin, Tu Hong-Hao, Strunz Walter T

机构信息

Institut für Theoretische Physik, Technische Universität Dresden, D-01062, Dresden, Germany.

出版信息

Phys Rev Lett. 2024 May 17;132(20):200403. doi: 10.1103/PhysRevLett.132.200403.

Abstract

Approaching the long-time dynamics of non-Markovian open quantum systems presents a challenging task if the bath is strongly coupled. Recent proposals address this problem through a representation of the so-called process tensor in terms of a tensor network. We show that for Gaussian environments highly efficient contraction to a matrix product operator (MPO) form can be achieved with infinite MPO evolution methods, leading to significant computational speed-up over existing proposals. The result structurally resembles open system evolution with carefully designed auxiliary degrees of freedom, as in hierarchical or pseudomode methods. Here, however, these degrees of freedom are generated automatically by the MPO evolution algorithm. Moreover, the semigroup form of the resulting propagator enables us to explore steady-state physics, such as phase transitions.

摘要

如果量子系统与环境强耦合,那么研究非马尔可夫开放量子系统的长期动力学将是一项具有挑战性的任务。最近的一些提议通过张量网络表示所谓的过程张量来解决这个问题。我们表明,对于高斯环境,使用无限矩阵乘积算符(MPO)演化方法可以高效地将其收缩为MPO形式,从而比现有提议显著提高计算速度。该结果在结构上类似于具有精心设计的辅助自由度的开放系统演化,如分层或赝模方法。然而,在这里,这些自由度是由MPO演化算法自动生成的。此外,所得传播子的半群形式使我们能够探索稳态物理,如相变。

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