局部纯化张量网络的林德布拉德动力学黎曼方法

Emiliano Godinez-Ramirez, Richard Milbradt, Christian B. Mendl
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引用次数: 0

摘要

张量网络为在具有近邻耦合的多体开放量子系统中实现林德布拉德动力学提供了一个宝贵的框架。特别是,被称为 "局部净化密度操作器"(Locally Purified DensityOperator)的张量网络解析利用密度矩阵的局部净化来保证状态在任何时候都是正的。在此框架内,耗散演化利用特罗特-铃木分裂,产生二阶近似误差。然而,由于林德布拉第动力学的性质,采用高阶方案会导致非物理量子通道。在这项工作中,我们利用量子通道的克劳斯表示中固有的规自由度来改善分裂误差。为此,我们在等距的黎曼流形上提出了一个优化问题,并通过二阶信任区域算法找到了解决方案。我们利用两个近邻噪声模型验证了我们的方法,与其他正向保留方案相比,我们的方法实现了数量级的改进。此外,我们还证明了我们的方法作为压缩方案的实用性,有助于控制计算资源的指数级增长,迄今为止,计算资源的指数级增长限制了局部纯化公式的使用。
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A Riemannian Approach to the Lindbladian Dynamics of a Locally Purified Tensor Network
Tensor networks offer a valuable framework for implementing Lindbladian dynamics in many-body open quantum systems with nearest-neighbor couplings. In particular, a tensor network ansatz known as the Locally Purified Density Operator employs the local purification of the density matrix to guarantee the positivity of the state at all times. Within this framework, the dissipative evolution utilizes the Trotter-Suzuki splitting, yielding a second-order approximation error. However, due to the Lindbladian dynamics' nature, employing higher-order schemes results in non-physical quantum channels. In this work, we leverage the gauge freedom inherent in the Kraus representation of quantum channels to improve the splitting error. To this end, we formulate an optimization problem on the Riemannian manifold of isometries and find a solution via the second-order trust-region algorithm. We validate our approach using two nearest-neighbor noise models and achieve an improvement of orders of magnitude compared to other positivity-preserving schemes. In addition, we demonstrate the usefulness of our method as a compression scheme, helping to control the exponential growth of computational resources, which thus far has limited the use of the locally purified ansatz.
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