Abstract
AbstractWe introduce multiple parametrized circuit ansätze and present the results of a numerical study comparing their performance with a standard Quantum Alternating Operator Ansatz approach. The ansätze are inspired by mixing and phase separation in the QAOA, and also motivated by compilation considerations with the aim of running on near-term superconducting quantum processors. The methods are tested on random instances of a quadratic binary constrained optimization problem that is fully connected for which the space of feasible solutions has constant Hamming weight.For the parameter setting strategies and evaluation metric used, the average performance achieved by the QAOA is effectively matched by the one obtained by a ”mixer-phaser” ansatz that can be compiled in less than half-depth of standard QAOA on most superconducting qubit processors.
Funder
Ames Research Center
Air Force Research Laboratory
Defense Advanced Research Projects Agency
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software
Cited by
8 articles.
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