• Corpus ID: 174802928

Quantum Approximate Optimization with a Trapped-Ion Quantum Simulator

@article{Pagano2019QuantumAO,
  title={Quantum Approximate Optimization with a Trapped-Ion Quantum Simulator},
  author={Guido Pagano and Aniruddha Bapat and Patrick Becker and K S Collins and Arinjoy De and Paul W Hess and Harvey B. Kaplan and Antonios Kyprianidis and Wen Lin Tan and Christopher L. Baldwin and Lucas T. Brady and Abhinav Deshpande and F. Liu and Stephen P. Jordan and Alexey V. Gorshkov and Christopher R. Monroe},
  journal={arXiv: Quantum Physics},
  year={2019}
}
Quantum computers and simulators may offer significant advantages over their classical counterparts, providing insights into quantum many-body systems and possibly solving exponentially hard problems, such as optimization and satisfiability. Here we report the first implementation of a shallow-depth Quantum Approximate Optimization Algorithm (QAOA) using an analog quantum simulator to estimate the ground state energy of the transverse field Ising model with tunable long-range interactions… 
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