Constructing neural stationary states for open quantum many-body systems

@article{Yoshioka2019ConstructingNS,
  title={Constructing neural stationary states for open quantum many-body systems},
  author={N. Yoshioka and R. Hamazaki},
  journal={Physical Review B},
  year={2019},
  volume={99},
  pages={214306}
}
We propose a new variational scheme based on the neural-network quantum states to simulate the stationary states of open quantum many-body systems. Using the high expressive power of the variational ansatz described by the restricted Boltzmann machines, which we dub as the neural stationary state ansatz, we compute the stationary states of quantum dynamics obeying the Lindblad master equations. The mapping of the stationary-state search problem into finding a zero-energy ground state of an… Expand
View PDF on arXiv
61 Citations
Highly Influential Citations
1
Background Citations
12
Methods Citations
7

Figures from this paper

61 Citations

Citation Type

Citation Type

Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems.
  • 67
  • PDF
Variational Neural-Network Ansatz for Steady States in Open Quantum Systems.
  • 64
  • PDF
Construct Stationary States Ansatz of Open Quantum Systems with Parameterized Quantum Circuits
Neural-Network Approach to Dissipative Quantum Many-Body Dynamics.
  • 71
  • PDF
Variational Quantum Algorithm for Non-equilibrium Steady States
  • 17
  • PDF
Neural-network quantum states at finite temperature
  • 3
  • PDF
Fermionic neural-network states for ab-initio electronic structure
  • 33
  • PDF
Restricted Boltzmann Machines for Quantum States with Non-Abelian or Anyonic Symmetries.
  • 16
  • PDF
Solving Quantum Master Equations with Deep Quantum Neural Networks
  • 4
  • PDF
Neural-Network Quantum States for the Electronic Structure of Real Solids
  • PDF
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 150 REFERENCES
Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems.
  • 67
  • PDF
Variational Neural-Network Ansatz for Steady States in Open Quantum Systems.
  • 64
  • PDF
Neural-Network Approach to Dissipative Quantum Many-Body Dynamics.
  • 71
  • PDF
Symmetries and Many-Body Excitations with Neural-Network Quantum States.
  • 59
  • PDF
Constructing exact representations of quantum many-body systems with deep neural networks
  • 61
  • PDF
Variational principle for steady states of dissipative quantum many-body systems.
  • H. Weimer
  • Physics, Medicine
  • Physical review letters
  • 2015
  • 93
  • PDF
Restricted Boltzmann machine learning for solving strongly correlated quantum systems
  • 114
  • PDF
Neural-Network Quantum States, String-Bond States, and Chiral Topological States
  • 116
  • PDF
Positive Tensor Network Approach for Simulating Open Quantum Many-Body Systems.
  • 72
  • PDF
Efficient representation of quantum many-body states with deep neural networks
  • 174
  • PDF
...
1
2
3
4
5
...