Analysis of a density matrix renormalization group approach for transport in open quantum systems

• URL: http://arxiv.org/abs/2009.08200v1
• Date: Thu, 17 Sep 2020 10:37:49 GMT
• Title: Analysis of a density matrix renormalization group approach for transport in open quantum systems
• Authors: Heitor P. Casagrande, Dario Poletti, Gabriel T. Landi
• Abstract summary: Density matrix renormalization group-based tools have been widely used in the study of closed systems. We present an implementation based on state-of-the-art matrix product state (MPS) and tensor network methods. We show that this implementation is suited for studying thermal transport in one-dimensional systems.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Understanding the intricate properties of one-dimensional quantum systems coupled to multiple reservoirs poses a challenge to both analytical approaches and simulation techniques. Fortunately, density matrix renormalization group-based tools, which have been widely used in the study of closed systems, have also been recently extended to the treatment of open systems. We present an implementation of such method based on state-of-the-art matrix product state (MPS) and tensor network methods, that produces accurate results for a variety of combinations of parameters. Unlike most approaches, which use the time-evolution to reach the steady-state, we focus on an algorithm that is time-independent and focuses on recasting the problem in exactly the same language as the standard Density Matrix Renormalization Group (DMRG) algorithm, initially put forward by M. C. Ba\~nuls et al. in Phys. Rev. Lett. 114, 220601 (2015). Hence, it can be readily exported to any of the available DMRG platforms. We show that this implementation is suited for studying thermal transport in one-dimensional systems. As a case study, we focus on the XXZ quantum spin chain and benchmark our results by comparing the spin current and magnetization profiles with analytical results. We then explore beyond what can be computed analytically. Our code is freely available on github at https://www.github.com/heitorc7/oDMRG.

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