Stationary states of dissipative systems using tensor network methods
06.02.2015 at 09:00
Tensor network states have proven successful in describing ground states of quantum many body systems. The paradigmatic example is that of Matrix Product States (MPS), which underlie the celebrated DMRG method for the
study of one dimensional systems. Using these methods it is also possible to simulate dynamics. MPS can be also extended to describe density operators. In the case of open systems, this extension has been combined with the evolution algorithms to find the stationary state under some Markovian dynamics. However, growing entanglement in the evolved state might represent a drawback for such strategy. We have devised a new variational algorithm to find a MPS description for the steady states of dissipative one dimensional systems. We have applied it to different dissipative spin chains and shown that the strategy allows for an efficient exploration of the nature of the steady state over a broad range of parameters.
A 450 - Theresienstr. 37