Adiabatic quantum optimization in the presence of discrete noise: Reducing the problem dimensionality

@article{Mandr2014AdiabaticQO,
  title={Adiabatic quantum optimization in the presence of discrete noise: Reducing the problem dimensionality},
  author={Salvatore Mandr{\`a} and Gian Giacomo Guerreschi and Al{\'a}n Aspuru-Guzik},
  journal={Physical Review A},
  year={2014},
  volume={92},
  pages={062320}
}
Adiabatic quantum optimization is a procedure to solve a vast class of optimization problems by slowly changing the Hamiltonian of a quantum system. The evolution time necessary for the algorithm to be successful scales inversely with the minimum energy gap encountered during the dynamics. Unfortunately, the direct calculation of the gap is strongly limited by the exponential growth in the dimensionality of the Hilbert space associated to the quantum system. Although many special-purpose… 

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