scholarly journals Cumulants and scaling functions of infinite matrix product states

2019 ◽  
Vol 100 (23) ◽  
Author(s):  
Jason C. Pillay ◽  
Ian P. McCulloch
Keyword(s):  
Scaling Functions ◽  
Infinite Matrix ◽  
Matrix Product ◽  
Matrix Product States

scholarly journals Integrable open spin chains related to infinite matrix product states

2016 ◽  
Vol 93 (15) ◽  
Author(s):  
B. Basu-Mallick ◽  
F. Finkel ◽  
A. González-López
Keyword(s):  
Spin Chains ◽  
Infinite Matrix ◽  
Matrix Product ◽  
Matrix Product States

scholarly journals Finite and infinite matrix product states for Gutzwiller projected mean-field wave functions

2021 ◽  
Vol 103 (12) ◽  
Author(s):  
Gabriel Petrica ◽  
Bo-Xiao Zheng ◽  
Garnet Kin-Lic Chan ◽  
Bryan K. Clark
Keyword(s):  
Mean Field ◽  
Wave Functions ◽  
Infinite Matrix ◽  
Matrix Product ◽  
Matrix Product States ◽  
Field Wave

scholarly journals Optimal sampling of dynamical large deviations via matrix product states

2021 ◽  
Vol 103 (6) ◽  
Author(s):  
Luke Causer ◽  
Mari Carmen Bañuls ◽  
Juan P. Garrahan
Keyword(s):  
Large Deviations ◽  
Matrix Product ◽  
Optimal Sampling ◽  
Matrix Product States

scholarly journals Using Matrix-Product States for Open Quantum Many-Body Systems: Efficient Algorithms for Markovian and Non-Markovian Time-Evolution

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 984
Author(s):  
Regina Finsterhölzl ◽  
Manuel Katzer ◽  
Andreas Knorr ◽  
Alexander Carmele
Keyword(s):  
Time Evolution ◽  
Nearest Neighbor ◽  
Matrix Product ◽  
Body System ◽  
Many Body ◽  
Initial State ◽  
Matrix Product States ◽  
Open Quantum ◽  
Many Body Systems ◽  
The Many

This paper presents an efficient algorithm for the time evolution of open quantum many-body systems using matrix-product states (MPS) proposing a convenient structure of the MPS-architecture, which exploits the initial state of system and reservoir. By doing so, numerically expensive re-ordering protocols are circumvented. It is applicable to systems with a Markovian type of interaction, where only the present state of the reservoir needs to be taken into account. Its adaption to a non-Markovian type of interaction between the many-body system and the reservoir is demonstrated, where the information backflow from the reservoir needs to be included in the computation. Also, the derivation of the basis in the quantum stochastic Schrödinger picture is shown. As a paradigmatic model, the Heisenberg spin chain with nearest-neighbor interaction is used. It is demonstrated that the algorithm allows for the access of large systems sizes. As an example for a non-Markovian type of interaction, the generation of highly unusual steady states in the many-body system with coherent feedback control is demonstrated for a chain length of N=30.

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