Variational Quantum Eigensolver for Frustrated Quantum Systems

@article{Uvarov2020VariationalQE,
  title={Variational Quantum Eigensolver for Frustrated Quantum Systems},
  author={Alexey Uvarov and Jacob D. Biamonte and Dmitry Yudin},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.00544}
}
Hybrid quantum-classical algorithms have been proposed as a potentially viable application of quantum computers. A particular example - the variational quantum eigensolver, or VQE - is designed to determine a global minimum in an energy landscape specified by a quantum Hamiltonian, which makes it appealing for the needs of quantum chemistry. Experimental realizations have been reported in recent years and theoretical estimates of its efficiency are a subject of intense effort. Here we consider… 

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References

SHOWING 1-10 OF 109 REFERENCES
and P
NAT
Apesar da gestão de carreiras ser uma preocupação recente no quadro da gestão das relações de trabalho, é hoje evidente a crise em que se encontra a forma tradicional de abordagem desta problemática.
d.
‘N’
  • P. Alam
  • Composites Engineering: An A–Z Guide
  • 2021
‘R’
  • P. Alam
  • Composites Engineering: An A–Z Guide
  • 2021
‘W’
  • P. Alam
  • Composites Engineering: An A–Z Guide
  • 2021
Chem.
  • Catalysis from A to Z
  • 2020
Generalization properties of neural network approximations to frustrated magnet ground states
TLDR
The authors show that limited generalization capacity of neural network representations of quantum states is responsible for convergence problems for frustrated systems.
Increasing the Representation Accuracy of Quantum Simulations of Chemistry without Extra Quantum Resources
Proposals for near-term experiments in quantum chemistry on quantum computers leverage the ability to target a subset of degrees of freedom containing the essential quantum behavior, sometimes called
Minimum hardware requirements for hybrid quantum–classical DMFT
TLDR
It is found quantum-classical DMFT calculations can be run on the next generation of NISQ devices if combined with the recompilation techniques developed in this work.
...
1
2
3
4
5
...