Abstract

Combinatorial optimization problems on graphs have broad applications in science and engineering. The quantum approximate optimization algorithm (QAOA) is a method to solve these problems on a quantum computer by applying multiple rounds of variational circuits. However, there exist several challenges limiting the application of QAOA to real-world problems. In this paper, we demonstrate on a trapped-ion quantum computer that QAOA results improve with the number of rounds for multiple problems on several arbitrary graphs. We also demonstrate an advanced mixing Hamiltonian that allows sampling of all optimal solutions with predetermined weights. Our results are a step toward applying quantum algorithms to real-world problems.

Publication Details
Publication Type
Journal Article
Year of Publication
2022
Volume
8
Issue
1
Number of Pages
015007
ISSN Number
2058-9565
DOI
10.1088/2058-9565/ac91ef
Journal
Quantum Science and Technology
Contributors