Hybrid Quantum-Classical QAOA Quantum Simulation with Trapped Atomic Ions
ORAL
Abstract
Hybrid quantum-classical algorithms, such as quantum approximate optimization algorithms (QAOA)\footnote{E. Farhi et al., arXiv:1411.4028v1}, are a promising tool to provide an approximate set of solutions to combinatorial optimization problems and to prepare non-trivial quantum states\footnote{W. W. Ho \& T. H. Hsieh, arXiv:1803.00026v3}. Here we report the implementation of a shallow-depth QAOA protocol with trapped atomic ions to compute the ground state energy of the transverse field Ising model with tunable long-range interactions. We performed an exhaustive search of the variational parameters to optimize the algorithm and investigated its performance as a function of system size. We plan to interface our quantum simulator with a classical optimization algorithm to find a set of parameters that minimize the energy output of QAOA.
*This work is supported by the DARPA program on Driven and Nonequilibrium Quantum Systems, the DOE program on Quantum Computing in Chemical and Material Sciences, the AFOSR MURI on Quantum Measurement and Verification, and the NSF Physics Frontier Center at JQI.
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