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Trapped Ion Quantum Computing
Quantum Simulation
Analysis of a density matrix renormalization group approach for transport in open quantum systems
arXiv
Authors: Heitor P. Casagrande, Dario Poletti, Gabriel T. Landi
Year
2020
Paper ID
20633
Status
Preprint
Abstract Read
~2 min
Abstract Words
209
Citations
N/A
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. Bañuls 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.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
- It adds a 2020 reference point for readers tracking recent quantum research.
- Understanding the intricate properties of one-dimensional quantum systems coupled to multiple reservoirs poses a challenge to both analytical approaches and simulation techniques.
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