Dimension truncation for open quantum systems in terms of tensor networks
arXiv preprint arXiv:1801.07418, 2018•arxiv.org
We present novel and simple estimation of a minimal dimension required for an effective
reservoir in open quantum systems. Using a tensor network formalism we introduce a new
object called a reservoir network (RN). The reservoir network is the tensor network in the
form of a Matrix Product State, which contains all effects of open dynamics. This object is
especially useful for understanding memory effects. We discuss possible applications of the
reservoir network and the estimation of dimension to develop new numerical and machine …
reservoir in open quantum systems. Using a tensor network formalism we introduce a new
object called a reservoir network (RN). The reservoir network is the tensor network in the
form of a Matrix Product State, which contains all effects of open dynamics. This object is
especially useful for understanding memory effects. We discuss possible applications of the
reservoir network and the estimation of dimension to develop new numerical and machine …
We present novel and simple estimation of a minimal dimension required for an effective reservoir in open quantum systems. Using a tensor network formalism we introduce a new object called a reservoir network (RN). The reservoir network is the tensor network in the form of a Matrix Product State, which contains all effects of open dynamics. This object is especially useful for understanding memory effects. We discuss possible applications of the reservoir network and the estimation of dimension to develop new numerical and machine learning based methods for open quantum systems.
arxiv.org
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